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Guide to Advanced Statistical Analysis in R


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

advanced statistics - don't panic!