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August 01, 2014
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Continuous Outcome Analyses

Download this set of examples

Type of Analysis Input file Data file View output
Exploratory factor analysis (EFA)
Holzinger-Swineford data, correlation matrix input cont1.inp holzcorr.dat cont1.std
Confirmatory factor analysis (CFA)
Holzinger-Swineford, raw data, bi-factor model cont14.inp holzingr.dat cont14.std
Factor analysis with covariates
1-factor model with covariates cont2.inp school.dat cont2.std
1-factor model with covariates and parameter equalities cont13.inp school.dat cont13.std
Classic SEM
Stability of alienation, Wheaton et al. (1977) cont3.inp wheacov.dat cont3.std
Multiple group analysis
MIMIC model cont4.inp school.dat cont4.std
MIMIC model with across group parameter equalities cont12.inp school.dat cont12.std
Growth modeling
Growth, parallel processes, regressions among the growth factors cont5.inp comp.dat cont5.std
Missing data analysis
MAR missingness, H0=H1,
bivariate apple crop data (n=18),
Little & Rubin (1987), p. 101
cont6.inp ft29.dat cont6.std
Complex sample analysis (aggregated or marginal modeling)
1-factor model with covariates (same model as cont2.inp, but taking clustering into account) cont7.inp school.dat cont7.std
Complex sample, aggregated, growth (same as cont5.inp, but taking clustering into account) cont8.inp comp.dat cont8.std
Multilevel modeling (disaggregated modeling)
Basic multilevel statistics, preparing for a 1-factor model with covariates (compare to cont2.inp), but only computing sample statistics: between- and within-covariance matrices and intraclass correlations cont9.inp school.dat cont9.std
1-factor model with covariates (compare to cont2.inp) cont10.inp school.dat cont10.std
3-level modeling, complex sample, disaggregated, growth (compare to cont5.inp) cont11.inp comp.dat cont11.std

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