Mplus Users Guide v6.. - Muthén & Muthén

TITLE, DATA, VARIABLE, And DEFINE Commandswhere gender, race, and educ are variables that are not used in theanalysis but that are saved in conjunction with the SAVEDATA and/orthe PLOT commands.In the second use, the AUXILIARY option is used in conjunction withTYPE=GENERAL with continuous dependent variables and maximumlikelihood estimation to identify a set of variables that will be used asmissing data correlates in addition to the analysis variables (Collins,Schafer, & Kam, 2001; Graham, 2003; Asparouhov & Muthén, 2008b;Enders, 2010). This use is not available with MODINDICES,BOOTSTRAP, and models with a set of exploratory factor analysis(EFA) factors in the MODEL command. The letter m in parentheses isplaced behind the variables in the AUXILIARY statement that will beused as missing data correlates. Following is an example of how tospecify the m setting:AUXILIARY = z1-z4 (m);where z1, z2, z3, and z4 are variables that will be used as missing datacorrelates.In the third use, the AUXILIARY option is used in conjunction withTYPE=MIXTURE to identify the variables for which the equality ofmeans across latent classes will be tested using posterior probabilitybasedmultiple imputations (Asparouhov, 2007). The letter e inparentheses is placed behind the variables in the AUXILIARY statementfor which equalities of means across latent classes will be tested.Following is an example of how to specify the e setting:AUXILIARY = race (e) ses (e) gender (e);where the equality of means for race, ses, and gender will be testedacross classes. The e setting and the r setting cannot be used in the sameanalysis.In the fourth use, the AUXILIARY option is used in conjunction withTYPE=MIXTURE to identify the covariates that are importantpredictors of latent classes. This is done using pseudo-class draws, thatis, the posterior-probability based multinomial logistic regression of acategorical latent variable on a set of covariates. The letter r in497