회귀, 경로 분석, 답사의 확실한 요인 분석 (EFA와 CFA), 구조 방정식 (SEM), 성장, 그리고 이산 및 연속 시간 생존 분석 모형을 추정
The Mplus Base Program estimates regression, path analysis, exploratory and confirmatory factor analysis (EFA and CFA), structural equation (SEM), growth, and discrete- and continuous-time survival analysis models. In regression and path analysis models, observed dependent variables can be continuous, censored, binary, ordered categorical (ordinal), counts, or a combination of these variable types. In addition, for regression analysis and path analysis for non-mediating variables, observed dependent variables can be unordered categorical (nominal). In EFA, factor indicators can be continuous, binary, ordered categorical (ordinal), or a combination of these variable types. In CFA, SEM, and growth models, observed dependent variables can be continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, or a combination of these variable types. Other special features include single or multiple group analysis; missing data estimation; complex survey data analysis including stratification, clustering, and unequal probabilities of selection (sampling weights); latent variable interactions and non-linear factor analysis using maximum likelihood; random slopes; individually-varying times of observation; non-linear parameter constraints; indirect effects; maximum likelihood estimation for all outcomes types; bootstrap standard errors and confidence intervals; Bayesian analysis and multiple imputation; Monte Carlo simulation facilities; and a post-processing graphics module.
