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Calcite | Level 5

Hi all,

I am working to fit an SEM model in which the dependent variable is binary. I am looking for literature on PROC CALIS for fitting SEM models where the dependent variable is binary. I look forward to any advise.

Lapis Lazuli | Level 10
Does this usage note from SAS help?
Calcite | Level 5
Hi All,
I am building an SEM model using PROC CALIS PATH analysis.
My dependent variable is HIV Status i.e either positive or negative.
Some of my other variables are categorical/binary e.g condom use (0/1), pregnant_ever (0/1)
In the model I put together, it seems to run but with the following error that suggests a poor fit "WARNING: Standard errors and t values might not be accurate with the use of the Moore-Penrose inverse."
I was wondering if someone can advise me on the best way to fix this error...or point me to some relevant literature fitting SEM PATH with a categorical dependent variable.

26 ods results on;
27 ods graphics on;
28 proc calis data=new_sib method=wls plots=pathdiagram;
29 path
37 IPV <--- violence,
38 client <--- violence,
39 police <--- violence,
40 childhood <--- violence,
42 ptsd <--- mental,
43 depression <--- mental,
49 binge_drinking <--- mental,
50 hiv <--- binge_drinking,
51 hiv <--- age_firstsw,
52 hiv <--- education,
53 hiv <--- born,
54 hiv <--- condom_use,
56 hiv <--- pregnant_ever;
2 The SAS System 17:13 Saturday, February 15, 2020
66 pathdiagram
67 diagram=standard;
68 fitindex on(only) = [chisq df probchi rmsea cn srmsr bentlercfi agfi] noindextype;
70 run;

WARNING: 74 of 3005 observations in data set WORK.NEW_SIB omitted due to missing values.
NOTE: Convergence criterion (GCONV=1E-8) satisfied.
NOTE: The Moore-Penrose inverse is used in computing the covariance matrix for parameter estimates.
WARNING: Standard errors and t values might not be accurate with the use of the Moore-Penrose inverse.
NOTE: PROCEDURE CALIS used (Total process time):
real time 2.01 seconds
cpu time 1.14 seconds

71 ods graphics on;
72 ods results off;


Kennedy Otwombe

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