ABOUT BOOK

Researchers often have difficulties collecting enough data to test their hypotheses, ~either because target groups are small or hard to access, or because data collection ~entails prohibitive costs. Such obstacles may result in data sets that are too small for ~the complexity of the statistical model needed to answer the research question. This ~unique book provides guidelines and tools for implementing solutions to issues ~that arise in small sample research. Each chapter illustrates statistical methods that ~allow researchers to apply the optimal statistical model for their research question ~when the sample is too small. ~This essential book will enable social and behavioral science researchers to test ~their hypotheses even when the statistical model required for answering their ~research question is too complex for the sample sizes they can collect. The statistical ~models in the book range from the estimation of a population mean to models with ~latent variables and nested observations, and solutions include both classical and ~Bayesian methods. All proposed solutions are described in steps researchers can ~implement with their own data and are accompanied with annotated syntax in R. ~The methods described in this book will be useful for researchers across the social ~and behavioral sciences, ranging from medical sciences and epidemiology to psychology, ~marketing, and economics.