Guide to Advanced Statistical Analysis in R
Contents
Chapter 1 structural equation modeling
- path analysis, confirmatory analysis, basic SEM, latent growth models
Chapter 2 time series analysis
- stationary and non-stationary data, ARIMA
- auto ARIMA, seasonal ARIMA (SARIMA)
Chapter 3 survival analysis
- life tables, Kaplan-Meier
- Cox model, Weibull and exponential distributions
Chapter 4 Longitudinal analysis
- repeated measures ANOVA, linear mixed effects model
- generalized estimating equations (GEE)
Chapter 5 multivariate analysis
- discriminant analysis, canonical correlation analysis
- multidimensional scaling
Chapter 6 miscellaneous methods
- GLM and Poisson regression, hierarchical modeling (multilevel models)
- power analysis, reliability
Other advanced tests
Many advanced tests not featured here appear in this book's sister volume,
Statistical Testing with R (second edition), or if you prefer not to use R, in the Vor Press books referring to jamovi.
Categorical tests include the binomial test, multinomial test (also known as Chi
squared Goodness of Fit), and log-linear analysis.
Other tests include logistic regression, MANOVA, principal components analysis,
exploratory factor analysis, cluster analysis and an introduction to Bayesian statistics.
Statistics without Mathematics series - General Editor: Cole Davis
ISBN numbers: Hardback - 978-1-915500-04-5 Paperback - 978-1-915500-03-8
Ebook - 978-1-915500-05-2
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