THEORY AND PRACTICE OF MIXED MODELING

Mixed modeling is popular in various fields including medicine and psychology, agriculture and other social sciences. This book first comprehensively handles the mathematical theory of mixed modeling. Data analysis dealing with some important data structures in mixed model analysis, including multilevel grouping, nested data, repeated measurements and cases of large data with over 1000 rows is handled, and all codes in R given explicitly. The "lmer" function ("lme4" package)in R-statistical software is the main analysis tool. R is a free software, yet very powerful, and has been embraced by many statistical data analysts. The book will be particularly helpfull to: (i) all statistics students who wish to link the theory of mixed modeling to data analysis and intrepretation, (ii) all researchers who are simply interested in mixed modeling analysis and reporting, (iii) it is a well illustrated case study, hence a very good teaching resource for students who wish to venture into real world statistical data analysis.

Autorentext

Nelson Owuor Onyango currently lecturers Statistics at the School of Mathematics, University of Nairobi, Kenya. He studied at the University of Nairobi(undergraduate and M.Sc. Statistics). He then proceeded to T.U. Munich in Germany for his PhD in Mathematics for Biosciences.