Maximum likelihood confirmatory factor analysis with robust estimation

TITLE:

section 5.14 data analysis example 3: confirmatory factor analysis with auxiliary variables and robust standard errors;

DATA:

file = eatingattitudes.dat;

VARIABLE:

! id = participant id;

! eat1-eat21 = eating attitudes test items;

! bmi = body mass index;

! wsb = western standards of beauty;

! anx = anxiety;

names = id eat1 eat2 eat10 eat11 eat12 eat14 eat24 eat3 eat18 eat21 bmi wsb anx;

usevariables = eat1 - eat21; 

auxiliary = (m) bmi - anx;  ! auxiliary variables;

missing are all (-99);

ANALYSIS:

estimator = mlr;  ! FIML with robust standard errors;

MODEL:

drive@1 foodpre@1;

drive by eat1-eat24*;

foodpre by eat3-eat21*;

OUTPUT:

standardized(stdyx) sampstat;

Questions or suggestions? Email Craig Enders