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Aggiungi al carrellogebundene Ausgabe. Condizione: Gut. 205 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 520.
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hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
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Aggiungi al carrelloHardcover. Condizione: Brand New. 1st edition. 205 pages. 9.50x6.50x0.50 inches. In Stock.
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Aggiungi al carrelloCondizione: New. pp. 224 Illus. This item is printed on demand.
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Peter L. BonateHow 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.
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 effortRequiring 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.