Chapter 7: Mixture Modeling with Cross-Sectional Data

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Example	View output	Download input	Download data	View Monte Carlo output	Download Monte Carlo input
7.1: Mixture regression analysis for a continuous dependent variable using automatic starting values with random starts	ex7.1	ex7.1.inp	ex7.1.dat	mcex7.1	mcex7.1.inp
7.2: Mixture regression analysis for a count variable using a zero-inflated Poisson model using automatic starting values with random starts	ex7.2	ex7.2.inp	ex7.2.dat	mcex7.2	mcex7.2.inp
7.3: LCA with binary latent class indicators using automatic starting values with random starts	ex7.3	ex7.3.inp	ex7.3.dat	mcex7.3	mcex7.3.inp
7.4: LCA with binary latent class indicators using user-specified starting values without random starts	ex7.4	ex7.4.inp	ex7.4.dat	mcex7.4	mcex7.4.inp
7.5: LCA with binary latent class indicators using user-specified starting values with random starts	ex7.5	ex7.5.inp	ex7.5.dat	mcex7.5	mcex7.5.inp
7.6: LCA with three-category latent class indicators using user-specified starting values without random starts	ex7.6	ex7.6.inp	ex7.6.dat	mcex7.6	mcex7.6.inp
7.7: LCA with unordered categorical latent class indicators using automatic starting values with random starts	ex7.7	ex7.7.inp	ex7.7.dat	mcex7.7	mcex7.7.inp
7.8: LCA with unordered categorical latent class indicators using user-specified starting values with random starts	ex7.8	ex7.8.inp	ex7.8.dat	mcex7.8	mcex7.8.inp
7.9: LCA with continuous latent class indicators using automatic starting values with random starts	ex7.9	ex7.9.inp	ex7.9.dat	mcex7.9	mcex7.9.inp
7.10: LCA with continuous latent class indicators using user-specified starting values without random starts	ex7.10	ex7.10.inp	ex7.10.dat	mcex7.10	mcex7.10.inp
7.11: LCA with binary, censored, unordered, and count latent class indicators using user-specified starting values without random starts	ex7.11	ex7.11.inp	ex7.11.dat	mcex7.11	mcex7.11.inp
7.12: LCA with binary latent class indicators using automatic starting values with random starts with a covariate and a direct effect	ex7.12	ex7.12.inp	ex7.12.dat	mcex7.12	mcex7.12.inp
7.13: Confirmatory LCA with binary latent class indicators and parameter constraints	ex7.13	ex7.13.inp	ex7.13.dat	mcex7.13	mcex7.13.inp
7.14: Confirmatory LCA with two categorical latent variables	ex7.14	ex7.14.inp	ex7.14.dat	mcex7.14	mcex7.14.inp
7.15: Loglinear model for a three-way table with conditional independence between the first two variables	ex7.15	ex7.15.inp	ex7.15.dat	mcex7.15	mcex7.15.inp
7.16: LCA with partial conditional independence	ex7.16	ex7.16.inp	ex7.16.dat	mcex7.16	mcex7.16.inp
7.17: Mixture CFA modeling	ex7.17	ex7.17.inp	ex7.17.dat	mcex7.17	mcex7.17.inp
7.18: LCA with a second-order factor (twin analysis)	ex7.18	ex7.18.inp	ex7.18.dat	mcex7.18	mcex7.18.inp
7.19: SEM with a categorical latent variable regressed on a continuous latent variable	ex7.19	ex7.19.inp	ex7.19.dat	mcex7.19	mcex7.19.inp
7.20: Structural equation mixture modeling	ex7.20	ex7.20.inp	ex7.20.dat	mcex7.20	mcex7.20.inp
7.21: Mixture modeling with known classes (multiple group analysis)	ex7.21	ex7.21.inp	ex7.21.dat	mcex7.21	mcex7.21.inp
7.22: Mixture modeling with continuous variables that correlate within class	ex7.22	ex7.22.inp	ex7.22.dat	mcex7.22	mcex7.22.inp
7.23: Mixture randomized trials modeling using CACE estimation with training data (data for this example cannot be created with Monte Carlo so only the input is provided)	none	ex7.23.inp	none	none	none
7.24: Mixture randomized trials modeling using CACE estimation with missing data on the latent class indicator	ex7.24	ex7.24.inp	ex7.24.dat	mcex7.24	mcex7.24.inp
7.25: Zero-inflated Poisson regression carried out as a two-class model	ex7.25	ex7.25.inp	ex7.25.dat	mcex7.25	mcex7.25.inp
7.26: CFA with a non-parametric representation of a non-normal factor distribution	ex7.26	ex7.26.inp	ex7.26.dat	mcex7.26	mcex7.26.inp
7.27: Factor (IRT) mixture analysis with binary latent class and factor indicators	ex7.27	ex7.27.inp	ex7.27.dat	mcex7.27	mcex7.27.inp
7.28: Two-group twin model for categorical outcomes using maximum likelihood and parameter constraints	ex7.28	ex7.28.inp	ex7.28.dat	mcex7.28	mcex7.28.inp
7.29: Two-group IRT twin model for factors with categorical factor indicators using parameter constraints	ex7.29	ex7.29.inp	ex7.29.dat	mcex7.29	mcex7.29.inp
7.30: Continuous-time survival analysis using a Cox regression model to estimate a treatment effect	ex7.30	ex7.30.inp	ex7.30.dat	mcex7.30	mcex7.30.inp

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