UCLA Academic Technology Services HomeServicesClassesContactJobs

Mplus FAQ
Which coefficients in a two-group regression or path model does Mplus constrain across groups by default?

The short answer:

None of the variables in a regression or path model (i.e. when all variables are manifest/observed), none of the parameters are constrained to equality by default.

An example with explanation:

Below is a simple two-group path model with an observed variable y regressed on three other observed variables, x1, x2, and x3.

    Data:
      File is D:\data\mydata.dat ;
    Variable:
      Names are female x3 x1 y x2;
        Missing are all (-9999) ;
      grouping is female (0 = male 1 = female);
    Analysis:
      Type = general ;
    Model:
        y on x1 x2 x3;

We have omitted most of the Mplus output file, to download the entire file click here: two_group_path_model.txt. Below is the MODEL RESULTS section for males and females (the output for males appears first, followed by the output for females). Comparing the regression coefficients (denoted ON), the intercept and the residual variances, we see that none of these coefficients are constrained to equality by default.

MODEL RESULTS

                                                    Two-Tailed
                    Estimate       S.E.  Est./S.E.    P-Value

Group MALE

 Y        ON
    X1                 0.352      0.105      3.365      0.001
    X2                 0.050      0.089      0.560      0.575
    X3                 0.450      0.105      4.307      0.000

 Intercepts
    Y                  8.205      4.798      1.710      0.087

 Residual Variances
    Y                 55.518      8.231      6.745      0.000




Group FEMALE

 Y        ON
    X1                 0.453      0.102      4.455      0.000
    X2                 0.046      0.084      0.546      0.585
    X3                 0.211      0.098      2.161      0.031

 Intercepts
    Y                 13.632      3.958      3.444      0.001

 Residual Variances
    Y                 43.290      5.864      7.382      0.000

How to cite this page

Report an error on this page

UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services


The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California.