Factor Analysis Action Set

factorAnalysis.faExtract <result=results> <status=rc> /

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

caslib="string",

compress=TRUE | FALSE,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

onDemand=TRUE | FALSE,

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

freq="variable-name",

fuzz=double,

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

method={name="ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters},

nFactors={integer-1 <, integer-2, ...>},

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=TRUE | FALSE,

replace=TRUE | FALSE

priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters},

referenceStructure=TRUE | FALSE,

reorder=TRUE | FALSE,

rotate={type="BIQUARTIMAX" | "BIQUARTIMIN" | "CF" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "NONE" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBLIMIN" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "ORTHOMAX" | "PARSIMAX" | "PROMAX" | "QUARTIMAX" | "QUARTIMIN" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "VARIMAX", type-specific-parameters},

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters},

name="table-name",

onDemand=TRUE | FALSE,

orderBy

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable

casLib="string"

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

name="table-name"

vars

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

weight="variable-name"

;

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
table	—	specifies the settings for an input table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
corrOut	—	specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes={{casinvardesc-1} <, {casinvardesc-2}, ...>}

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

For more information about specifying the attributes parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

Aliases	attribute
Aliases	attr

corrOut={casouttable}

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

display={displayTables}

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

freq="variable-name"

specifies a numeric variable that contains the frequency of occurrence of each observation.

fuzz=double

specifies a minimum threshold that determines whether to print correlations and factor loading values. Factor loadings whose absolute values less are than the specified threshold are printed as missing.

Minimum value	0

inputs={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies variables to use for analysis.

For more information about specifying the inputs parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

Aliases	input
	vars
	var

method={name="ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters}

specifies the method to be used for factor extraction.

The value that you specify for the name parameter determines the other parameters that apply.

Default	name="PRINCIPAL"
Alias

* nFactors={integer-1 <, integer-2, ...>}

specifies the number of factors to be extracted for each BY group. If the analysis does not use BY groups, or if you want to extract the same number of factors for all BY groups, then you can specify a single integer.

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters}

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default	SMC

referenceStructure=TRUE | FALSE

when set to True, requests output tables that are related to the reference structure. This parameter has no effect when you specify an orthogonal rotation.

Aliases	referenceStruct
	refStructure
	refStruct
Default	FALSE

reorder=TRUE | FALSE

when set to True, reorders the rows (variables) of various factor matrices in the output. Variables whose highest absolute loading (reference structure loading for oblique rotations) is on the first factor are displayed first, from largest to smallest loading, followed by variables whose highest absolute loading is on the second factor, and so on.

Default	FALSE

rotate={type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX" | "CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "NONE" | "OBLIMIN" | "ORTHOMAX" | "PROMAX", type-specific-parameters}

specifies the method to use for factor rotation.

The value that you specify for the type parameter determines the other parameters that apply.

Default	NONE

table={castable}

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias	varDef
Default	DF

DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for name="ALPHA"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

Parameters for name="ML"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

nObs=64-bit-integer

specifies the number of observations to be used for maximum likelihood or unweighted least squares factor extraction.

Minimum value	2

Parameters for name="PRINCIPAL"

No parameters apply when you specify PRINCIPAL.

Parameters for name="PRINIT"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

Parameters for name="ULS"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

nObs=64-bit-integer

specifies the number of observations to be used for maximum likelihood or unweighted least squares factor extraction.

Minimum value	2

Parameters for type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX"

No parameters apply when you specify BIQUARTIMAX.

Parameters for type="CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON"

oblique=TRUE | FALSE

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	FALSE

* weights={double-1 <, double-2, ...>}

specifies the two weights to use for traditional Crawford-Ferguson rotation.

Parameters for type="GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON"

oblique=TRUE | FALSE

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	FALSE

* weights={double-1 <, double-2, ...>}

specifies the four weights to use for generalized Crawford-Ferguson rotation.

Parameters for type="OBLIMIN"

tau=double

specifies the weight for the oblimin rotation.

Default	0

Parameters for type="ORTHOMAX"

gamma=double

specifies the weight for the orthomax rotation.

Default	1

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* values={double-1 <, double-2, ...>}

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

seed=64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default	0

Parameters for type="SMC"

No parameters apply when you specify SMC.

Parameters for type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

Parameters for type="CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

oblique=TRUE | FALSE

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	FALSE

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

* weights={double-1 <, double-2, ...>}

specifies the two weights to use for traditional Crawford-Ferguson rotation.

Parameters for type="GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

oblique=TRUE | FALSE

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	FALSE

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

* weights={double-1 <, double-2, ...>}

specifies the four weights to use for generalized Crawford-Ferguson rotation.

Parameters for type="NONE"

No parameters apply when you specify NONE.

Parameters for type="OBLIMIN"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

tau=double

specifies the weight for the oblimin rotation.

Default	0

Parameters for type="ORTHOMAX"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

gamma=double

specifies the weight for the orthomax rotation.

Default	1

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

Parameters for type="PROMAX"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

power=integer

specifies the power to be used to form the promax rotation target pattern.

Default	3
Minimum value	1

prerotate={type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX" | "CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "OBLIMIN" | "ORTHOMAX", type-specific-parameters}

specifies the prerotation method to use with the promax rotation.

The value that you specify for the type parameter determines the other parameters that apply.

promaxnorm=TRUE | FALSE

when set to True, uses row normalization of the prerotated factor pattern, which is used in computing the promax target matrix.

Default	TRUE

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

faExtract Action

Extracts common factors.

Lua Syntax

results, info = s:factorAnalysis_faExtract{

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

caslib="string",

compress=true | false,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

onDemand=true | false,

promote=true | false,

replace=true | false,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

caseSensitive=true | false,

exclude=true | false,

excludeAll=true | false,

keyIsPath=true | false,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=true | false

freq="variable-name",

fuzz=double,

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

method={name="ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters},

nFactors={integer-1 <, integer-2, ...>},

groupByVarsRaw=true | false,

includeAll=true | false,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=true | false,

replace=true | false

priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters},

referenceStructure=true | false,

reorder=true | false,

caslib="string",

computedOnDemand=true | false,

computedVars

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=true | false,

orderBy

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable

casLib="string"

name="table-name"

vars

={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

weight="variable-name"

}

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
table	—	specifies the settings for an input table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
corrOut	—	specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes={{casinvardesc-1} <, {casinvardesc-2}, ...>}

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

For more information about specifying the attributes parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

Aliases	attribute
Aliases	attr

corrOut={casouttable}

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

display={displayTables}

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

freq="variable-name"

specifies a numeric variable that contains the frequency of occurrence of each observation.

fuzz=double

Minimum value	0

inputs={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies variables to use for analysis.

For more information about specifying the inputs parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

Aliases	input
	vars
	var

method={name="ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters}

specifies the method to be used for factor extraction.

The value that you specify for the name parameter determines the other parameters that apply.

Default	name="PRINCIPAL"
Alias

* nFactors={integer-1 <, integer-2, ...>}

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters}

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default	SMC

referenceStructure=true | false

when set to True, requests output tables that are related to the reference structure. This parameter has no effect when you specify an orthogonal rotation.

Aliases	referenceStruct
	refStructure
	refStruct
Default	false

reorder=true | false

Default	false

rotate={type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX" | "CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "NONE" | "OBLIMIN" | "ORTHOMAX" | "PROMAX", type-specific-parameters}

specifies the method to use for factor rotation.

The value that you specify for the type parameter determines the other parameters that apply.

Default	NONE

table={castable}

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias	varDef
Default	DF

DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for name="ALPHA"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

Parameters for name="ML"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

nObs=64-bit-integer

specifies the number of observations to be used for maximum likelihood or unweighted least squares factor extraction.

Minimum value	2

Parameters for name="PRINCIPAL"

No parameters apply when you specify PRINCIPAL.

Parameters for name="PRINIT"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

Parameters for name="ULS"

convergence=double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

heywood="BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

maxIterations=64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

nObs=64-bit-integer

specifies the number of observations to be used for maximum likelihood or unweighted least squares factor extraction.

Minimum value	2

Parameters for type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX"

No parameters apply when you specify BIQUARTIMAX.

Parameters for type="CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON"

oblique=true | false

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	false

* weights={double-1 <, double-2, ...>}

specifies the two weights to use for traditional Crawford-Ferguson rotation.

Parameters for type="GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON"

oblique=true | false

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	false

* weights={double-1 <, double-2, ...>}

specifies the four weights to use for generalized Crawford-Ferguson rotation.

Parameters for type="OBLIMIN"

tau=double

specifies the weight for the oblimin rotation.

Default	0

Parameters for type="ORTHOMAX"

gamma=double

specifies the weight for the orthomax rotation.

Default	1

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* values={double-1 <, double-2, ...>}

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

seed=64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default	0

Parameters for type="SMC"

No parameters apply when you specify SMC.

Parameters for type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

Parameters for type="CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

oblique=true | false

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	false

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

* weights={double-1 <, double-2, ...>}

specifies the two weights to use for traditional Crawford-Ferguson rotation.

Parameters for type="GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

oblique=true | false

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	false

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

* weights={double-1 <, double-2, ...>}

specifies the four weights to use for generalized Crawford-Ferguson rotation.

Parameters for type="NONE"

No parameters apply when you specify NONE.

Parameters for type="OBLIMIN"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

tau=double

specifies the weight for the oblimin rotation.

Default	0

Parameters for type="ORTHOMAX"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

gamma=double

specifies the weight for the orthomax rotation.

Default	1

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

Parameters for type="PROMAX"

convergence=double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

maxIterations=64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

normalization="COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

power=integer

specifies the power to be used to form the promax rotation target pattern.

Default	3
Minimum value	1

prerotate={type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX" | "CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "OBLIMIN" | "ORTHOMAX", type-specific-parameters}

specifies the prerotation method to use with the promax rotation.

The value that you specify for the type parameter determines the other parameters that apply.

promaxnorm=true | false

when set to True, uses row normalization of the prerotated factor pattern, which is used in computing the promax target matrix.

Default	true

singular=double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

faExtract Action

Extracts common factors.

Python Syntax

results=s.factorAnalysis.faExtract(

=[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"caslib":"string",

"compress":True | False,

"indexVars":["variable-name-1" <, "variable-name-2", ...>],

"label":"string",

"lifetime":64-bit-integer,

"maxMemSize":64-bit-integer,

"memoryFormat":"DVR" | "INHERIT" | "STANDARD",

"name":"table-name",

"onDemand":True | False,

"promote":True | False,

"replace":True | False,

"replication":integer,

"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE",

"threadBlockSize":64-bit-integer,

"timeStamp":"string",

"where":["string-1" <, "string-2", ...>]

"caseSensitive":True | False,

"exclude":True | False,

"excludeAll":True | False,

"keyIsPath":True | False,

"names":["string-1" <, "string-2", ...>],

"pathType":"LABEL" | "NAME",

"traceNames":True | False

freq="variable-name",

fuzz=double,

=[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

method={"name":"ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters},

nFactors=[integer-1 <, integer-2, ...>],

"groupByVarsRaw":True | False,

"includeAll":True | False,

"names":["string-1" <, "string-2", ...>] | {"key-1":{casouttable-1} <, "key-2":{casouttable-2}, ...>},

"repeated":True | False,

"replace":True | False

priors={"type":"ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters},

referenceStructure=True | False,

reorder=True | False,

rotate={"type":"BIQUARTIMAX" | "BIQUARTIMIN" | "CF" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "NONE" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBLIMIN" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "ORTHOMAX" | "PARSIMAX" | "PROMAX" | "QUARTIMAX" | "QUARTIMIN" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "VARIMAX", type-specific-parameters},

"caslib":"string",

"computedOnDemand":True | False,

"computedVars"

:[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"groupBy"

:[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"groupByMode":"NOSORT" | "REDISTRIBUTE",

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters},

"name":"table-name",

"onDemand":True | False,

"orderBy"

:[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars"

:[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable"

"casLib":"string"

"dataSourceOptions":{adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

"name":"table-name"

"vars"

:[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

weight="variable-name"

)

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
table	—	specifies the settings for an input table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
corrOut	—	specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes=[{casinvardesc-1} <, {casinvardesc-2}, ...>]

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

For more information about specifying the attributes parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

Aliases	attribute
Aliases	attr

corrOut={casouttable}

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

display={displayTables}

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

freq="variable-name"

specifies a numeric variable that contains the frequency of occurrence of each observation.

fuzz=double

Minimum value	0

inputs=[{casinvardesc-1} <, {casinvardesc-2}, ...>]

specifies variables to use for analysis.

For more information about specifying the inputs parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

Aliases	input
	vars
	var

method={"name":"ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters}

specifies the method to be used for factor extraction.

The value that you specify for the name parameter determines the other parameters that apply.

Default	name="PRINCIPAL"
Alias

* nFactors=[integer-1 <, integer-2, ...>]

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

priors={"type":"ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters}

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default	SMC

referenceStructure=True | False

when set to True, requests output tables that are related to the reference structure. This parameter has no effect when you specify an orthogonal rotation.

Aliases	referenceStruct
	refStructure
	refStruct
Default	False

reorder=True | False

Default	False

rotate={"type":"BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX" | "CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "NONE" | "OBLIMIN" | "ORTHOMAX" | "PROMAX", type-specific-parameters}

specifies the method to use for factor rotation.

The value that you specify for the type parameter determines the other parameters that apply.

Default	NONE

table={castable}

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias	varDef
Default	DF

DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for name="ALPHA"

"convergence":double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

"heywood":"BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

"maxIterations":64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

Parameters for name="ML"

"convergence":double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

"heywood":"BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

"maxIterations":64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

"nObs":64-bit-integer

specifies the number of observations to be used for maximum likelihood or unweighted least squares factor extraction.

Minimum value	2

Parameters for name="PRINCIPAL"

No parameters apply when you specify PRINCIPAL.

Parameters for name="PRINIT"

"convergence":double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

"heywood":"BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

"maxIterations":64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

Parameters for name="ULS"

"convergence":double

specifies the convergence criterion to be used for an iterative factor extraction algorithm.

Alias	conv
Default	0.001
Minimum value	0

"heywood":"BOUND" | "STOP" | "UNBOUND"

specifies the method to be used to handle Heywood cases.

Default	STOP

BOUND

specifies that communalities should be set to 1 when a Heywood case is encountered.

STOP

specifies that the factor extraction algorithm should stop when a Heywood case is encountered.

UNBOUND

specifies that the extraction should continue even if a prior communality is estimated to be greater than 1.

"maxIterations":64-bit-integer

specifies the maximum number of iterations for an iterative factor extraction algorithm.

Aliases	maxIter
Aliases	maxIters
Default	30
Minimum value	1

"nObs":64-bit-integer

specifies the number of observations to be used for maximum likelihood or unweighted least squares factor extraction.

Minimum value	2

Parameters for type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX"

No parameters apply when you specify BIQUARTIMAX.

Parameters for type="CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON"

"oblique":True | False

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	False

* "weights":[double-1 <, double-2, ...>]

specifies the two weights to use for traditional Crawford-Ferguson rotation.

Parameters for type="GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON"

"oblique":True | False

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	False

* "weights":[double-1 <, double-2, ...>]

specifies the four weights to use for generalized Crawford-Ferguson rotation.

Parameters for type="OBLIMIN"

"tau":double

specifies the weight for the oblimin rotation.

Default	0

Parameters for type="ORTHOMAX"

"gamma":double

specifies the weight for the orthomax rotation.

Default	1

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* "values":[double-1 <, double-2, ...>]

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

"seed":64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default	0

Parameters for type="SMC"

No parameters apply when you specify SMC.

Parameters for type="BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX"

"convergence":double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

"maxIterations":64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

"normalization":"COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

"singular":double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

Parameters for type="CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON"

"convergence":double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

"maxIterations":64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

"normalization":"COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

"oblique":True | False

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	False

"singular":double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

* "weights":[double-1 <, double-2, ...>]

specifies the two weights to use for traditional Crawford-Ferguson rotation.

Parameters for type="GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON"

"convergence":double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

"maxIterations":64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

"normalization":"COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

"oblique":True | False

when set to True, specifies an oblique Crawford-Ferguson rotation.

Default	False

"singular":double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

* "weights":[double-1 <, double-2, ...>]

specifies the four weights to use for generalized Crawford-Ferguson rotation.

Parameters for type="NONE"

No parameters apply when you specify NONE.

Parameters for type="OBLIMIN"

"convergence":double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

"maxIterations":64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

"normalization":"COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

"singular":double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

"tau":double

specifies the weight for the oblimin rotation.

Default	0

Parameters for type="ORTHOMAX"

"convergence":double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

"gamma":double

specifies the weight for the orthomax rotation.

Default	1

"maxIterations":64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

"normalization":"COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

"singular":double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

Parameters for type="PROMAX"

"convergence":double

specifies the convergence criterion value for factor rotation cycles. Rotation stops when the scaled change of the simplicity function value is less than the specified value.

Alias	conv
Default	1E-09
Minimum value	0

"maxIterations":64-bit-integer

specifies the maximum number of iterations for the factor rotation algorithm. The default value is either 10 times the number of variables or 100, whichever is greater.

Aliases	maxIter
Aliases	maxIters
Minimum value	1

"normalization":"COV" | "KAISER" | "NONE" | "WEIGHT"

specifies the method of normalizing the rows of the factor pattern for rotation.

Alias	norm
Default	KAISER

COV

rescales the rows of the pattern matrix to represent covariances instead of correlations.

KAISER

specifies Kaiser's normalization.

NONE

specifies that normalization is not performed.

Alias	RAW

WEIGHT

specifies that rows are weighted by the Cureton-Mulaik technique.

"power":integer

specifies the power to be used to form the promax rotation target pattern.

Default	3
Minimum value	1

"prerotate":{"type":"BIQUARTIMAX" | "BIQUARTIMIN" | "COVARIMIN" | "EQUAMAX" | "FACTORPARSIMAX" | "OBBIQUARTIMAX" | "OBEQUAMAX" | "OBFACTORPARSIMAX" | "OBPARSIMAX" | "OBQUARTIMAX" | "OBVARIMAX" | "PARSIMAX" | "QUARTIMAX" | "QUARTIMIN" | "VARIMAX" | "CF" | "TRADITIONALCF" | "TRADITIONALCRAWFORDFERGUSON" | "GCF" | "GENCF" | "GENERALIZEDCF" | "GENERALIZEDCRAWFORDFERGUSON" | "OBLIMIN" | "ORTHOMAX", type-specific-parameters}

specifies the prerotation method to use with the promax rotation.

The value that you specify for the type parameter determines the other parameters that apply.

"promaxnorm":True | False

when set to True, uses row normalization of the prerotated factor pattern, which is used in computing the promax target matrix.

Default	True

"singular":double

specifies the singularity criterion for oblique rotations.

Alias	sing
Default	1E-08
Minimum value	0

faExtract Action

Extracts common factors.

R Syntax

results <– cas.factorAnalysis.faExtract(s,

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

=list(

caslib="string",

compress=TRUE | FALSE,

indexVars=list("variable-name-1" <, "variable-name-2", ...>),

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

onDemand=TRUE | FALSE,

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where=list("string-1" <, "string-2", ...>)

=list(

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>),

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

freq="variable-name",

fuzz=double,

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

method=list(name="ALPHA" | "ML" | "PRINCIPAL" | "PRINIT" | "ULS", name-specific-parameters),

nFactors=list(integer-1 <, integer-2, ...>),

=list(

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>) | list(key-1=list(casouttable-1) <, key-2=list(casouttable-2), ...>),

repeated=TRUE | FALSE,

replace=TRUE | FALSE

referenceStructure=TRUE | FALSE,

reorder=TRUE | FALSE,

=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

groupBy

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=TRUE | FALSE,

orderBy

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable

=list(

casLib="string"

name="table-name"

vars

=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)