@@ -232,6 +232,129 @@ function CommandExecutor() {

}

]

},

"logit":{

"parameters":"depvar indepvarlist [, options]",

"shortDescription":"Displays logistic regression for the variables.",

"description":"The command logit fits a logit model for a binary response by maximum likelihood; it models the probability of a positive outcome given a set of regressors. depvar equal to nonzero and nonmissing (typically depvar equal to one) indicates a positive outcome, whereas depvar equal to zero indicates a negative outcome. Depvar must be a binomial variable and factor variable is supported.",

"syntax":"logit depvar indepvarlist [, options]",

"examples":[

{

"example":"logit income2004 income2003",

"description":"Displays logistic regression model for income2004 based on income2003 with default confidence interval level set at 95%."

"description":"Displays logistic regression model for the levels of income2003 interacted with the levels of income2004 based on income2002 with confidence interval level set at 95%."

}

],

"options":[

{

"name":"noconstant",

"shortDescription":"Suppress constant term",

"description":"Suppresses the constant term (the y intercept) in the model"

},

{

"name":"or",

"shortDescription":"report odds ratios",

"description":"Report the odds ratios instead of coefficient in the coefficient table"

},

{

"name":"level(#)",

"shortDescription":"Set confidence level; default is level(95)",

"description":"Specifies the confidence level, as a percentage, for confidence intervals. The default is set at 95% and can be set to desired via this."

}

]

},

"mlogit":{

"parameters":"depvar indepvarlist [, options]",

"shortDescription":"Displays multinomial (polytomous) logistic regression for the variables.",

"description":"The command mlogit fits maximum-likelihood multinomial logit models, also known as polytomous logis- tic regression. You can define constraints to perform constrained estimation. Some people refer to conditional logistic regression as multinomial logit. Factor variable is supported.",

"description":"Displays multinomial logistic regression model for the levels of income2003 interacted with the levels of income2004 based on income2002 with confidence interval level set at 95%."

}

],

"options":[

{

"name":"noconstant",

"shortDescription":"Suppress constant term",

"description":"Suppresses the constant term (the y intercept) in the model"

},

{

"name":"or",

"shortDescription":"report odds ratios",

"description":"Report the odds ratios instead of coefficient in the coefficient table"

},

{

"name":"level(#)",

"shortDescription":"Set confidence level; default is level(95)",

"description":"Specifies the confidence level, as a percentage, for confidence intervals. The default is set at 95% and can be set to desired via this."

}

]

},

"probit":{

"parameters":"depvar indepvarlist [, options]",

"shortDescription":"Displays Probit regression for the variables.",

"description":"The command probit fits maximum-likelihood probit models. Depvar must be a binomial variable and factor variable is supported.",

"description":"Displays probit regression model for the levels of income2003 interacted with the levels of income2004 based on income2002 with confidence interval level set at 95%."

}

],

"options":[

{

"name":"noconstant",

"shortDescription":"Suppress constant term",

"description":"Suppresses the constant term (the y intercept) in the model"

},

{

"name":"or",

"shortDescription":"report odds ratios",

"description":"Report the odds ratios instead of coefficient in the coefficient table"

},

{

"name":"level(#)",

"shortDescription":"Set confidence level; default is level(95)",

"description":"Specifies the confidence level, as a percentage, for confidence intervals. The default is set at 95% and can be set to desired via this."

}

]

},

"replace":{

"parameters":"oldvar = expression [if ...]",

"shortDescription":"Modify contents of existing variable as per the expression defined.",