{ "item_title" : "Analysing Experiments with Mixed-Effects Models", "item_author" : [" Johannes Forkman "], "item_description" : "Focusing on mixed-effects models, this book offers a comprehensive guide to analysing experiments across diverse fields, including behavioural, agricultural, and medical sciences. The text opens with a traditional analysis of variance and then ranges from linear fixed-effects models to generalised linear mixed-effects models. It covers the most common experimental designs, such as factorial, hierarchical, between-subject, within-subject, cross-over, two-factor mixed, and split-plot designs, before studying analysis of covariance, models with group-specific error variances and models for repeated-measures analysis. Frequently drawing on real-life experiments, the book offers 69 examples and 134 exercises. Readers are supported with digital supplements, comprising the solutions to exercises, the datasets and R code and SAS code for all examples requiring software computation. This is an essential resource for students, practitioners conducting experiments and applied statisticians wishing to use mixed-effects models for the analysis of experiments.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/00/983/752/1009837524_b.jpg", "price_data" : { "retail_price" : "85.00", "online_price" : "85.00", "our_price" : "85.00", "club_price" : "85.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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