Logistic regression using clustering PreviousNext
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 mplususer posted on Saturday, January 04, 2014 - 12:19 am
(My apologies if this has already been asked.)

I am using MPlus 4.0. I would like to conduct a logistic regression analysis, and my data are clustered at the family level.

The following logistic regression (without accounting for clustering) runs with no problems:

Title:
Logistic regression for suicide attempts - MDD onset/recurrence
Data:
File is "file";
Variable:
Names are
IDYRFAM ID IDSEX MDDADOL MDDREC MDDGRP1 MDDGRP2 MDDGRP3
MDDGRP4 MDDGRP F3SUIC F3PABU F3SABU;
Usevar are
IDSEX MDDADOL MDDREC F3SUIC;
Categorical are
F3SUIC;
Missing are all (-99);
Analysis:
ESTIMATOR = ML;
Model: F3SUIC on IDSEX MDDADOL MDDREC;
Output: CINTERVAL;

However, when I include CLUSTER = IDYRFAM, I am told I must use TYPE = COMPLEX. When I add TYPE = COMPLEX, I am told that ESTIMATOR = ML cannot be used with TYPE = COMPLEX. My understanding is that the command ESTIMATOR = ML is what determines that this analysis is a logistic regression.

Is there anyway to run a logistic regression with clustered data in MPlus 4.0? If not, can one do so in a later version of MPlus?

Thank you very much for your help.
 Linda K. Muthen posted on Saturday, January 04, 2014 - 11:44 am
Try ESTIMATOR=MLR;
 mplususer posted on Saturday, January 04, 2014 - 1:38 pm
That worked, thank you very much for your reply. I am now running the following:

Title:
Logistic regression for suicide attempts - MDD onset/recurrence
Data:
File is "file";
Variable:
Names are
IDYRFAM ID IDSEX MDDADOL MDDREC MDDGRP1 MDDGRP2 MDDGRP3
MDDGRP4 MDDGRP F3SUIC F3PABU F3SABU;
Usevar are
IDYRFAM IDSEX MDDADOL MDDREC F3SUIC;
Categorical are
F3SUIC;
CLUSTER = IDYRFAM;
Missing are all (-99);
Analysis:
ESTIMATOR = MLR;
TYPE = COMPLEX;
Model: F3SUIC on IDSEX MDDADOL MDDREC;
Output: CINTERVAL;

I was hoping to ask one more question. It looks like later versions of MPlus give two-tailed p-values for the estimates. Is it possible to request p-values in MPlus 4.0? Or is there a way for me to calculate the p-values for the estimates with the information given?

Thanks again for your help.
 Linda K. Muthen posted on Saturday, January 04, 2014 - 4:38 pm
No, there are no p-values in Version 4. The ratio of the parameter estimate to the standard error is a z-value in large samples. You can look it up in a z-table to getthe p-value.
 mplususer posted on Sunday, January 05, 2014 - 12:49 pm
Of course. Thanks again!
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