This course introduces Structural equation modeling (SEM) with Stata software. This statistical method tests theoretically derived models with observed and unobserved variables.  This methodology is different from other regression models in that this method does not assume that the variables have been measured without error. The relationship between theoretical constructs is tested using latent variables, which are variables with at least two observable measures that mathematically can represent unobserved abstract constructs. The relationship between variables is analyzed using direct, indirect, and total effects.  In this manner, researchers can test mediation effects to identify underlying mechanisms that influence the relationship between a key independent variable and outcome. Moreover, this type of model allows researchers to test theoretical models that have more than one dependent variable. The class will focus on models for continuous variables and discuss options to analyze models with categorical variables.

The course will cover how to perform the following steps:

1.       Measure confirmatory factor analysis (CFA) to evaluate the validity of the construct

2.       Model identification

3.       Model fit

4.       Test hypotheses

5.       Model the missing data of continuous independent variables

6.       Interpret results

Requirements: 1) Students must know how to model and interpret correlations and ordinary least square (OLS) regressions. 2) Know how to use the basic Stata functions, i.e., enter and save data, create variables, use command window, and do file. 3) Knowledge of logistic regression models is not required but is helpful.