Multiple Linear Regression (MLR) Example - 01-2 Multiple Outcomes
Multiple Linear Regression (MLR) Example - 01-2 Multiple Outcomes
Tags: Linear Regression, Multiple Predictors, Multiple Outcomes, Mplus
2019-01-30
Abstract: This guide outlines how to fit a linear regression model using Mplus. The results of the linear model (seven predictors and two outcomes) fitted with Mplus can be compared to the same model fitted with lavaan (see Multiple Linear Regression Example in lavaan - 01).
Table of Contents
1 TITLE Command
This example is for multiple linear regression conducted in Mplus.
TITLE: Example 4 - Multiple Linear Regression - 01-2 Multiple Outcomes
2 DATA Command
Nothing changes with the data importation.
DATA: FILE IS "../../data/job_placement.csv";
3 VARIABLE Command
The data are imported the same way as before, but notice the change under the USEVARIABLES ARE statement.
VARIABLE: NAMES ARE id wjcalc wjspl wratspl wratcalc waiscalc waisspl edlevel newschl suspend expelled haveld female age; USEVARIABLES ARE wjspl wjcalc edlevel newschl suspend expelled haveld female age; MISSING ARE all(99999);
4 MODEL Command
The only thing that is new in this example is in the MODEL command. Here the MLR model is specified with three lines. The ON command tells Mplus to regress the two outcome variables on the right side onto the variables on the left side. In this model there are seven variables used as predictors of wjspl and wjcalc.
MODEL: wjspl ON edlevel newschl suspend expelled haveld female age; wjcalc ON edlevel newschl suspend expelled haveld female age;
5 Run the Model
mplus reg-01-2.inp
Mplus VERSION 8.2 (Linux) MUTHEN & MUTHEN Running input file 'reg-01-2.inp'... Beginning Time: 13:55:47 Ending Time: 13:55:47 Elapsed Time: 00:00:00 Refer to 'reg-01-2.out' for warning(s).
6 Review the Results
Click reg-01-2.out to see the output.