Mplus Users Guide v6.. - Muthén & Muthén

Examples: Regression And Path AnalysisCHAPTER 3EXAMPLES: REGRESSION ANDPATH ANALYSISRegression analysis with univariate or multivariate dependent variablesis a standard procedure for modeling relationships among observedvariables. Path analysis allows the simultaneous modeling of severalrelated regression relationships. In path analysis, a variable can be adependent variable in one relationship and an independent variable inanother. These variables are referred to as mediating variables. For bothtypes of analyses, observed dependent variables can be continuous,censored, binary, ordered categorical (ordinal), counts, or combinationsof these variable types. In addition, for regression analysis and pathanalysis for non-mediating variables, observed dependent variables canbe unordered categorical (nominal).For continuous dependent variables, linear regression models are used.For censored dependent variables, censored-normal regression modelsare used, with or without inflation at the censoring point. For binary andordered categorical dependent variables, probit or logistic regressionmodels are used. Logistic regression for ordered categorical dependentvariables uses the proportional odds specification. For unorderedcategorical dependent variables, multinomial logistic regression modelsare used. For count dependent variables, Poisson regression models areused, with or without inflation at the zero point. Both maximumlikelihood and weighted least squares estimators are available.All regression and path analysis models can be estimated using thefollowing special features:• Single or multiple group analysis• Missing data• Complex survey data• Random slopes• Linear and non-linear parameter constraints• Indirect effects including specific paths• Maximum likelihood estimation for all outcome types• Bootstrap standard errors and confidence intervals19