9780367221898_text (1).pdf
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 mode...
Γλώσσα: | English |
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Έκδοση: |
Taylor & Francis
2020
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Περίληψη: | 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. |
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