Description
Book Synopsis: How do you analyze pretest-posttest data? Difference scores? Percent change scores? ANOVA? In medical, psychological, sociological, and educational studies, researchers often design experiments in which they collect baseline (pretest) data prior to randomization. However, they often find it difficult to decide which method of statistical analysis is most appropriate to use. Until now, consulting the available literature would prove a long and arduous task, with papers sparsely scattered throughout journals and textbook references few and far between.
Analysis of Pretest-Posttest Designs brings welcome relief from this conundrum. This one-stop reference - written specifically for researchers - answers the questions and helps clear the confusion about analyzing pretest-posttest data. Keeping derivations to a minimum and offering real life examples from a range of disciplines, the author gathers and elucidates the concepts and techniques most useful for studies incorporating baseline data.
Understand the pros and cons of different methods - ANOVA, ANCOVA, percent change, difference scores, and moreLearn to choose the most appropriate statistical test - Numerous Monte Carlo simulations compare the various tests and help you select the one best suited to your dataTackle more difficult analyses - The extensive SAS code included saves you programming time and effort
Requiring just a basic background in statistics and experimental design, this book incorporates most, if not all of the reference material that deals with pretest-posttest data. If you use baseline data in your studies, Analysis of Pretest-Posttest Designs will save you time, increase your understanding, and ultimately improve the interpretation and analysis of your data.
Details
Are you struggling with analyzing pretest-posttest data? Unsure which statistical analysis method to use? Look no further! Introducing Analysis of Pretest-Posttest Designs, the ultimate reference guide for researchers like you. This comprehensive resource eliminates the confusion by providing clear answers and real-life examples from various disciplines. Say goodbye to scouring through scattered papers and textbooks - our book gathers and explains the most useful concepts and techniques for studies incorporating baseline data.
With Analysis of Pretest-Posttest Designs, you'll gain a deep understanding of different methods such as ANOVA, ANCOVA, percent change, and difference scores. Our book goes even further by comparing these methods through Monte Carlo simulations, allowing you to select the most appropriate test for your data. No more guesswork or uncertainty!
What sets Analysis of Pretest-Posttest Designs apart is its accessibility. You don't need an advanced statistical background to benefit from this book. It presents the material in a straightforward manner, making it easy to grasp for researchers of all levels. Plus, we've included extensive SAS code that will save you valuable programming time and effort for more complex analyses.
Save time, increase your understanding, and enhance the interpretation and analysis of your data with Analysis of Pretest-Posttest Designs. Don't miss out on this essential resource for anyone using baseline data in their studies. Get your copy today and revolutionize your research!
Click here to get Analysis of Pretest-Posttest Designs and take your data analysis to the next level!
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