By Peter L. Bonate

How do you research pretest-posttest facts? distinction rankings? percentage switch ratings? ANOVA? In clinical, mental, sociological, and academic reports, researchers usually layout experiments within which they gather baseline (pretest) information ahead of randomization. even if, they typically locate it tricky to make your mind up which approach to statistical research is most excellent to take advantage of. formerly, consulting the to be had literature might turn out an extended and laborious activity, with papers in moderation scattered all through journals and textbook references few and much between.

Analysis of Pretest-Posttest Designs brings welcome reduction from this conundrum. This one-stop reference - written in particular for researchers - solutions the questions and is helping transparent the confusion approximately interpreting pretest-posttest information. protecting derivations to a minimal and delivering genuine lifestyles examples from a variety of disciplines, the writer gathers and elucidates the innovations and methods most respected for reports incorporating baseline data.

Understand the professionals and cons of other tools - ANOVA, ANCOVA, percentage switch, distinction rankings, and more

Learn to decide on the main applicable statistical try - various Monte Carlo simulations evaluate a number of the exams and assist you opt for the only most fitted for your data

Tackle tougher analyses - The broad SAS code integrated saves you programming time and effort

Requiring only a uncomplicated heritage in statistics and experimental layout, this publication contains so much, if no longer the entire reference fabric that offers with pretest-posttest info. if you happen to use baseline info on your stories, research of Pretest-Posttest Designs will prevent time, elevate your knowing, and finally increase the translation and research of your data.

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Analysis of Pretest-Posttest Designs by Peter L. Bonate

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