[PDF.89nq] Linear Mixed-Effects Models Using R: A Step-by-Step Approach (Springer Texts in Statistics)

Linear Mixed-Effects Models Using R: A Step-by-Step Approach (Springer Texts in Statistics)

[PDF.kq36] Linear Mixed-Effects Models Using R: A Step-by-Step Approach (Springer Texts in Statistics)

Linear Mixed-Effects Models Using  Andrzej Galecki, Tomasz Burzykowski epub
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 | #223966 in Books |  Springer |  2013-02-05 | Original language:English | PDF # 1 |  9.21 x1.25 x6.14l,2.15 | File type: PDF | 542 pages

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||4 of 6 people found the following review helpful.| the authors write in great clarity and have chosen to exemplify the different nuances ...|By OmniReader|Outstanding, the authors write in great clarity and have chosen to exemplify the different nuances of the approach on data sets that have different configurations (time-bound, clustered, hierarchical, etc.) which makes for a very thorough coverage of the topic. The way that R| ||From the reviews:|Overall, this is very well-written book that covers both LMs and LMMs. Most of the R codes have been checked and work well. The R package nlmeU created by the authors provides great convenience for readers to explore the data in the textbook

Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help reade...

You easily download any file type for your gadget.Linear Mixed-Effects Models Using R: A Step-by-Step Approach (Springer Texts in Statistics)   |  Andrzej Galecki, Tomasz Burzykowski. A good, fresh read, highly recommended.

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