Ebook: Behavioral Research Data Analysis with R
Author: Yuelin Li Jonathan Baron (auth.)
- Tags: Statistics for Social Science Behavorial Science Education Public Policy and Law
- Series: Use R!
- Year: 2012
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples. The book will also help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant to researchers in others fields that do similar kinds of research.
The authors emphasize practical data analytic skills so that they can be quickly incorporated into readers’ own research.
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples. The book will also help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant to researchers in others fields that do similar kinds of research.
The authors emphasize practical data analytic skills so that readers can quickly incorporated the data in their own research.
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples. The book will also help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant to researchers in others fields that do similar kinds of research.
The authors emphasize practical data analytic skills so that readers can quickly incorporated the data in their own research.
Content:
Front Matter....Pages i-xii
Introduction....Pages 1-17
Reading and Transforming Data Format....Pages 19-37
Statistics for Comparing Means and Proportions....Pages 39-54
R Graphics and Trellis Plots....Pages 55-77
Analysis of Variance: Repeated-Measures....Pages 79-107
Linear and Logistic Regression....Pages 109-127
Statistical Power and Sample Size Considerations....Pages 129-137
Item Response Theory....Pages 139-159
Imputation of Missing Data....Pages 161-175
Linear Mixed-Effects Models in Analyzing Repeated-Measures Data....Pages 177-204
Linear Mixed-Effects Models in Cluster-Randomized Studies....Pages 205-227
Back Matter....Pages 229-245
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples. The book will also help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant to researchers in others fields that do similar kinds of research.
The authors emphasize practical data analytic skills so that readers can quickly incorporated the data in their own research.
Content:
Front Matter....Pages i-xii
Introduction....Pages 1-17
Reading and Transforming Data Format....Pages 19-37
Statistics for Comparing Means and Proportions....Pages 39-54
R Graphics and Trellis Plots....Pages 55-77
Analysis of Variance: Repeated-Measures....Pages 79-107
Linear and Logistic Regression....Pages 109-127
Statistical Power and Sample Size Considerations....Pages 129-137
Item Response Theory....Pages 139-159
Imputation of Missing Data....Pages 161-175
Linear Mixed-Effects Models in Analyzing Repeated-Measures Data....Pages 177-204
Linear Mixed-Effects Models in Cluster-Randomized Studies....Pages 205-227
Back Matter....Pages 229-245
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