Common Parameter: modelStatement

CASL Syntax

modelStatement={
censor="variable-name",
depVars={{
name="variable-name",
options={modelopts}
}, {...}},
dist="BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL",
effects={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
entry="variable-name",
group={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
include=integer | {{effect-1} <, {effect-2}, ...>},
informative=TRUE | FALSE,
link="CLOGLOG" | "GLOGIT" | "IDENTITY" | "LOG" | "LOGIT" | "LOGLOG" | "NORMIT" | "POWER" | "POWERMINUS2" | "RECIPROCAL" | "ZERO",
noint=TRUE | FALSE,
offset="variable-name",
start=integer | {{effect-1} <, {effect-2}, ...>},
subject={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
trial="variable-name"
}

Parameter Descriptions

censor="variable-name"

specifies the censor variable.

depVars={{responsevar-1} <, {responsevar-2}, ...>}

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases depVar
target

The responsevar value can be one or more of the following:

name="variable-name"

names the response variable.

options={modelopts}

specifies a list of parameters for the response variable.

The modelopts value can be one or more of the following:

descending=TRUE | FALSE

when set to True, reverses the sort order of the response categories. When the descending parameter is set to True and a value is specified for the order parameter, the action orders the response categories according to the requested order and then reverses that order.

Default FALSE
event="FIRST" | "LAST" | double | "string"

specifies the event category for the binary response model. FIRST and LAST refer to the first and last ordered value of the response, respectively.

levelType="BINARY" | "INTERVAL" | "NOMINAL" | "ORDINAL"

specifies the type of the response variable. The types NOMINAL, ORDINAL and BINARY specify that the response variable should be levelized. When the value of this parameter is INTERVAL, all other parameters specified for this response variable are ignored and the response variable is not levelized.

Default INTERVAL
order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the response variable. This ordering determines which parameters in the model correspond to each level in the data.

ref="FIRST" | "LAST" | double | "string"

specifies the reference level that is used for the response variable. Valid parameter values are a quoted string that specifies a valid level for the response variable or FIRST or LAST. FIRST and LAST refer to the first and last ordered value of the variable, respectively.

dist="BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL"

specifies the response distribution for the model.

effects={{effect-1} <, {effect-2}, ...>}

specifies a list of effects that define the model. Each term in this list is made up of variables specified in the vars parameter and their interaction (which can be NONE, CROSS, or BAR). When the interaction is BAR, it can be limited by the maxInteract parameter.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

entry="variable-name"

specifies the entry variable.

group={{effect-1} <, {effect-2}, ...>}

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

include=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

informative=TRUE | FALSE

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default FALSE

specifies the link function for the model.

noint=TRUE | FALSE

when set to True, does not include the intercept term in the model.

Default FALSE
offset="variable-name"

specifies a numeric offset variable. This variable cannot be a classification variable, a response variable, or one of the explanatory variables.

start=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

subject={{effect-1} <, {effect-2}, ...>}

identifies the subjects in a mixed model.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

trial="variable-name"

specifies a positive numeric variable that is the number of trials. When you specify a trial variable, the response variable is called the events variable and it must contain the number of positive responses (or events).

Lua Syntax

modelStatement={
censor="variable-name",
depVars={{
name="variable-name",
options={modelopts}
}, {...}},
dist="BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL",
effects={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
entry="variable-name",
group={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
include=integer | {{effect-1} <, {effect-2}, ...>},
informative=true | false,
link="CLOGLOG" | "GLOGIT" | "IDENTITY" | "LOG" | "LOGIT" | "LOGLOG" | "NORMIT" | "POWER" | "POWERMINUS2" | "RECIPROCAL" | "ZERO",
noint=true | false,
offset="variable-name",
start=integer | {{effect-1} <, {effect-2}, ...>},
subject={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
trial="variable-name"
}

Parameter Descriptions

censor="variable-name"

specifies the censor variable.

depVars={{responsevar-1} <, {responsevar-2}, ...>}

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases depVar
target

The responsevar value can be one or more of the following:

name="variable-name"

names the response variable.

options={modelopts}

specifies a list of parameters for the response variable.

The modelopts value can be one or more of the following:

descending=true | false

when set to True, reverses the sort order of the response categories. When the descending parameter is set to True and a value is specified for the order parameter, the action orders the response categories according to the requested order and then reverses that order.

Default false
event="FIRST" | "LAST" | double | "string"

specifies the event category for the binary response model. FIRST and LAST refer to the first and last ordered value of the response, respectively.

levelType="BINARY" | "INTERVAL" | "NOMINAL" | "ORDINAL"

specifies the type of the response variable. The types NOMINAL, ORDINAL and BINARY specify that the response variable should be levelized. When the value of this parameter is INTERVAL, all other parameters specified for this response variable are ignored and the response variable is not levelized.

Default INTERVAL
order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the response variable. This ordering determines which parameters in the model correspond to each level in the data.

ref="FIRST" | "LAST" | double | "string"

specifies the reference level that is used for the response variable. Valid parameter values are a quoted string that specifies a valid level for the response variable or FIRST or LAST. FIRST and LAST refer to the first and last ordered value of the variable, respectively.

dist="BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL"

specifies the response distribution for the model.

effects={{effect-1} <, {effect-2}, ...>}

specifies a list of effects that define the model. Each term in this list is made up of variables specified in the vars parameter and their interaction (which can be NONE, CROSS, or BAR). When the interaction is BAR, it can be limited by the maxInteract parameter.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

entry="variable-name"

specifies the entry variable.

group={{effect-1} <, {effect-2}, ...>}

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

include=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

informative=true | false

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default false

specifies the link function for the model.

noint=true | false

when set to True, does not include the intercept term in the model.

Default false
offset="variable-name"

specifies a numeric offset variable. This variable cannot be a classification variable, a response variable, or one of the explanatory variables.

start=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

subject={{effect-1} <, {effect-2}, ...>}

identifies the subjects in a mixed model.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

trial="variable-name"

specifies a positive numeric variable that is the number of trials. When you specify a trial variable, the response variable is called the events variable and it must contain the number of positive responses (or events).

Python Syntax

modelStatement={
"censor":"variable-name",
"depVars":[{
"name":"variable-name",
"options":{modelopts}
}<, {...}>],
"dist":"BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL",
"effects":[{
"interaction":"BAR" | "CROSS" | "NONE",
"maxInteract":integer,
"nest":["string-1" <, "string-2", ...>],
required parameter "vars":["string-1" <, "string-2", ...>]
}<, {...}>],
"entry":"variable-name",
"group":[{
"interaction":"BAR" | "CROSS" | "NONE",
"maxInteract":integer,
"nest":["string-1" <, "string-2", ...>],
required parameter "vars":["string-1" <, "string-2", ...>]
}<, {...}>],
"include":integer | [{effect-1} <, {effect-2}, ...>],
"informative":True | False,
"link":"CLOGLOG" | "GLOGIT" | "IDENTITY" | "LOG" | "LOGIT" | "LOGLOG" | "NORMIT" | "POWER" | "POWERMINUS2" | "RECIPROCAL" | "ZERO",
"noint":True | False,
"offset":"variable-name",
"start":integer | [{effect-1} <, {effect-2}, ...>],
"subject":[{
"interaction":"BAR" | "CROSS" | "NONE",
"maxInteract":integer,
"nest":["string-1" <, "string-2", ...>],
required parameter "vars":["string-1" <, "string-2", ...>]
}<, {...}>],
"trial":"variable-name"
}

Parameter Descriptions

"censor":"variable-name"

specifies the censor variable.

"depVars":[{responsevar-1} <, {responsevar-2}, ...>]

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases depVar
target

The responsevar value can be one or more of the following:

"name":"variable-name"

names the response variable.

"options":{modelopts}

specifies a list of parameters for the response variable.

The modelopts value can be one or more of the following:

"descending":True | False

when set to True, reverses the sort order of the response categories. When the descending parameter is set to True and a value is specified for the order parameter, the action orders the response categories according to the requested order and then reverses that order.

Default False
"event":"FIRST" | "LAST" | double | "string"

specifies the event category for the binary response model. FIRST and LAST refer to the first and last ordered value of the response, respectively.

"levelType":"BINARY" | "INTERVAL" | "NOMINAL" | "ORDINAL"

specifies the type of the response variable. The types NOMINAL, ORDINAL and BINARY specify that the response variable should be levelized. When the value of this parameter is INTERVAL, all other parameters specified for this response variable are ignored and the response variable is not levelized.

Default INTERVAL
"order":"FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the response variable. This ordering determines which parameters in the model correspond to each level in the data.

"ref":"FIRST" | "LAST" | double | "string"

specifies the reference level that is used for the response variable. Valid parameter values are a quoted string that specifies a valid level for the response variable or FIRST or LAST. FIRST and LAST refer to the first and last ordered value of the variable, respectively.

"dist":"BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL"

specifies the response distribution for the model.

"effects":[{effect-1} <, {effect-2}, ...>]

specifies a list of effects that define the model. Each term in this list is made up of variables specified in the vars parameter and their interaction (which can be NONE, CROSS, or BAR). When the interaction is BAR, it can be limited by the maxInteract parameter.

The effect value can be one or more of the following:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

"entry":"variable-name"

specifies the entry variable.

"group":[{effect-1} <, {effect-2}, ...>]

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

The effect value can be one or more of the following:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

"include":integer | [{effect-1} <, {effect-2}, ...>]

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

"informative":True | False

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default False

specifies the link function for the model.

"noint":True | False

when set to True, does not include the intercept term in the model.

Default False
"offset":"variable-name"

specifies a numeric offset variable. This variable cannot be a classification variable, a response variable, or one of the explanatory variables.

"start":integer | [{effect-1} <, {effect-2}, ...>]

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

"subject":[{effect-1} <, {effect-2}, ...>]

identifies the subjects in a mixed model.

The effect value can be one or more of the following:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

"trial":"variable-name"

specifies a positive numeric variable that is the number of trials. When you specify a trial variable, the response variable is called the events variable and it must contain the number of positive responses (or events).

R Syntax

modelStatement=list(
censor="variable-name",
depVars=list( list(
name="variable-name",
options=list(modelopts)
) <, list(...)>),
dist="BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL",
effects=list( list(
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest=list("string-1" <, "string-2", ...>),
required parameter vars=list("string-1" <, "string-2", ...>)
) <, list(...)>),
entry="variable-name",
group=list( list(
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest=list("string-1" <, "string-2", ...>),
required parameter vars=list("string-1" <, "string-2", ...>)
) <, list(...)>),
include=integer | list( list(effect-1) <, list(effect-2), ...>),
informative=TRUE | FALSE,
link="CLOGLOG" | "GLOGIT" | "IDENTITY" | "LOG" | "LOGIT" | "LOGLOG" | "NORMIT" | "POWER" | "POWERMINUS2" | "RECIPROCAL" | "ZERO",
noint=TRUE | FALSE,
offset="variable-name",
start=integer | list( list(effect-1) <, list(effect-2), ...>),
subject=list( list(
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest=list("string-1" <, "string-2", ...>),
required parameter vars=list("string-1" <, "string-2", ...>)
) <, list(...)>),
trial="variable-name"
)

Parameter Descriptions

censor="variable-name"

specifies the censor variable.

depVars=list( list(responsevar-1) <, list(responsevar-2), ...>)

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases depVar
target

The responsevar value can be one or more of the following:

name="variable-name"

names the response variable.

options=list(modelopts)

specifies a list of parameters for the response variable.

The modelopts value can be one or more of the following:

descending=TRUE | FALSE

when set to True, reverses the sort order of the response categories. When the descending parameter is set to True and a value is specified for the order parameter, the action orders the response categories according to the requested order and then reverses that order.

Default FALSE
event="FIRST" | "LAST" | double | "string"

specifies the event category for the binary response model. FIRST and LAST refer to the first and last ordered value of the response, respectively.

levelType="BINARY" | "INTERVAL" | "NOMINAL" | "ORDINAL"

specifies the type of the response variable. The types NOMINAL, ORDINAL and BINARY specify that the response variable should be levelized. When the value of this parameter is INTERVAL, all other parameters specified for this response variable are ignored and the response variable is not levelized.

Default INTERVAL
order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the response variable. This ordering determines which parameters in the model correspond to each level in the data.

ref="FIRST" | "LAST" | double | "string"

specifies the reference level that is used for the response variable. Valid parameter values are a quoted string that specifies a valid level for the response variable or FIRST or LAST. FIRST and LAST refer to the first and last ordered value of the variable, respectively.

dist="BERNOULLI" | "BETA" | "BINOMIAL" | "EXPONENTIAL" | "GAMMA" | "GAUSSIAN" | "GENPOISSON" | "GEOMETRIC" | "IGAUSSIAN" | "MULTINOMIAL" | "NEGBINOMIAL" | "POISSON" | "STUDENT" | "TWEEDIE" | "WEIBULL"

specifies the response distribution for the model.

effects=list( list(effect-1) <, list(effect-2), ...>)

specifies a list of effects that define the model. Each term in this list is made up of variables specified in the vars parameter and their interaction (which can be NONE, CROSS, or BAR). When the interaction is BAR, it can be limited by the maxInteract parameter.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

entry="variable-name"

specifies the entry variable.

group=list( list(effect-1) <, list(effect-2), ...>)

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

include=integer | list( list(effect-1) <, list(effect-2), ...>)

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

informative=TRUE | FALSE

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default FALSE

specifies the link function for the model.

noint=TRUE | FALSE

when set to True, does not include the intercept term in the model.

Default FALSE
offset="variable-name"

specifies a numeric offset variable. This variable cannot be a classification variable, a response variable, or one of the explanatory variables.

start=integer | list( list(effect-1) <, list(effect-2), ...>)

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

subject=list( list(effect-1) <, list(effect-2), ...>)

identifies the subjects in a mixed model.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Default NONE
maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

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

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

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

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

trial="variable-name"

specifies a positive numeric variable that is the number of trials. When you specify a trial variable, the response variable is called the events variable and it must contain the number of positive responses (or events).

Last updated: March 05, 2026