OM DENNE EPISODE
Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance and multiple linear regression models. This short course features an introduction to the logic of SEM, the assumptions and required input for SEM analysis, and how to perform SEM analyses using the AMOS (Analysis of Moment Structures) software. We also will cover time–related latent variables, the use of modification indices and critical ratio in exploratory analyses, computation of implied moments, factor score weights, total effects, and indirect effects.
Course files available here: www.lisa.stat.vt.edu/?q=node/4875.
Course files available here: www.lisa.stat.vt.edu/?q=node/4875.
Engelsk
USA
UDSKRIFT 🔗
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SØK BLANT TIDLIGERE EPISODER
Søk etter gamle episoder av LISA: Laboratory for Interdisciplinary Statistical Analysis - Short Courses.
ANDRE EPISODE I DENNE PODKAST
Visualizing your data is an essential first step for any statistical analysis and often times the graph itself provides the best statistical interpretation of the data. This course will present principles of good graphics and provide examples to help you answer your research question graphically u…
R is a free computing and graphical software/environment for statistical analysis. Part III of this short course consists of 3 sections:
Section 5 introduces the concept of generalized linear models. R will be used for performing logistic regression and Poisson regression.
Section 6 intro…
R is a free computing and graphical software/environment for statistical analysis. Part II of this short course consists of 2 sections:
Section 3 introduces statistical analysis in R, including t-tests, ANOVA, linear regression, nonparametric tests, and logistic regression.
Section 4 conta…
R is a free computing and graphical software/environment for statistical analysis. Part III of this short course consists of 3 sections:
Section 5 introduces the concept of generalized linear models. R will be used for performing logistic regression and Poisson regression.
Section 6 intro…
Ansvarsfraskrivelse: Podkasten og kunstværket, det finnes indlejret på denne siden, er fra LISA, som tilhører dens eier og ikke er tilknyttet eller godkjent av Listen Notes, Inc.
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