Covariance Analysis For Split Plot And Split Block Designs And Computer Packages

A complete and up-to-date discussion of optimal split plot and split block designs Variations on Split Plot and Split Block Experiment Designs provides a comprehensive treatment of the design and analysis of two types of trials that are extremely popular in practice and play an integral part in the screening of applied experimental designs--split plot and split block experiments. Illustrated with numerous examples, this book presents a theoretical background and provides two and three error terms, a thorough review of the recent work in the area of split plot and split blocked experiments, and a number of significant results. Written by renowned specialists in the field, this book features: * Discussions of non-standard designs in addition to coverage of split block and split plot designs * Two chapters on combining split plot and split block designs and missing observations, which are unique to this book and to the field of study * SAS? commands spread throughout the book, which allow readers to bypass tedious computation and reveal startling observations * Detailed formulae and thorough remarks at the end of each chapter * Extensive data sets, which are posted on the book's FTP site The design and analysis approach advocated in Variations on Split Plot and Split Block Experiment Designs is essential in creating tailor-made experiments for applied statisticians from industry, medicine, agriculture, chemistry, and other fields of study.

In order to provide an understanding of covariance analyses for split plot designs, analyses are first conducted on a data set without the covariate. Then an analysis with the covariate is performed. The third example has a different experiment design for the whole plots and the covariate is constant for all split plots within the whole plot. Computer packages may only give portions of the analysis correctly. Some packages require two procedural calls to obtain a portion of the correct results. BMDP 2V falls in the above category. Keywords: Analysis of variance; Experimental design.