Mplus Users Guide v6.. - Muthén & Muthén

Examples: Confirmatory Factor Analysis AndStructural Equation ModelingVARIABLE:NAMES ARE y1-y6;The VARIABLE command is used to provide information about thevariables in the data set to be analyzed. The NAMES option is used toassign names to the variables in the data set. The data set in thisexample contains six variables: y1, y2, y3, y4, y5, y6. Note that thehyphen can be used as a convenience feature in order to generate a list ofnames.MODEL:f1 BY y1-y3;f2 BY y4-y6;The MODEL command is used to describe the model to be estimated.Here the two BY statements specify that f1 is measured by y1, y2, andy3, and f2 is measured by y4, y5, and y6. The metric of the factors is setautomatically by the program by fixing the first factor loading in eachBY statement to 1. This option can be overridden. The intercepts andresidual variances of the factor indicators are estimated and the residualsare not correlated as the default. The variances of the factors areestimated as the default. The factors are correlated as the defaultbecause they are independent (exogenous) variables. The defaultestimator for this type of analysis is maximum likelihood. TheESTIMATOR option of the ANALYSIS command can be used to selecta different estimator.EXAMPLE 5.2: CFA WITH CATEGORICAL FACTORINDICATORSTITLE: this is an example of a CFA withcategorical factor indicatorsDATA: FILE IS ex5.2.dat;VARIABLE: NAMES ARE u1-u6;CATEGORICAL ARE u1-u6;MODEL: f1 BY u1-u3;f2 BY u4-u6;The difference between this example and Example 5.1 is that the factorindicators are binary or ordered categorical (ordinal) variables instead ofcontinuous variables. The CATEGORICAL option is used to specifywhich dependent variables are treated as binary or ordered categorical(ordinal) variables in the model and its estimation. In the example57