Advanced Statistics for Physical and Occupational Therapy

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Advanced Statistics for Physical and Occupational Therapy explains the basis for statistical analyses that are commonly used to answer clinical research questions related to physical and occupational therapy. This textbook provides a resource to help students and faculty in physical and occupational therapy graduate programs understand the basis for common statistical analyses and be able to apply these techniques in their own research. This textbook provides readers with the basis for common statistical analyses, including t-tests, analysis of variance, regression, and nonparametric tests. Each chapter includes step-by-step tutorials with corresponding example data sets explaining how to conduct these statistical analyses using Statistical Package for the Social Sciences (SPSS) software and the Excel Analysis ToolPak, as well as how to identify and interpret relevant output and report results.

Advanced Statistics for Physical and Occupational Therapy is key reading for students in physical therapy, occupational therapy, sport performance, and sport rehabilitation graduate programs as well as students in athletic training courses, applied statistics in sport, and research methods in sport modules.

This new text will also be of interest to practicing clinicians who hope to better understand the research they are reading and/or are interested in starting to conduct their own clinical research.

Author(s): Thomas Gus Almonroeder
Publisher: Routledge
Year: 2022

Language: English
Pages: 261
City: New York

Cover
Half Title
Title
Copyright
Contents
List of Figures
List of Tables
List of Boxes
Preface
Glossary
1 Introduction to fundamental concepts
2 Descriptive statistics
3 The normal distribution
4 Probability and statistical inference
5 t-tests
6 Introduction to analysis of variance
7 Factorial analysis of variance
8 Correlation
9 Simple linear regression
10 Multiple regression
11 Logistic regression
12 Non-parametric tests
13 Effect sizes and confidence intervals
14 Sample size estimation
15 Analysis of covariance
16 Multivariate analysis of variance
Data Sets
Appendixes
References
Index