Statistical Strategies for Small Sample Research / Edition 1

by Rick H. Hoyle

Overview

This book provides encouragement and strategies for researchers who routinely address research questions using data from small samples. Chapters cover such topics as: using multiple imputation software with small sets; computing and combining effect sizes; bootstrap hypothesis testing; application of latent variable modeling; time-series data from small numbers of individuals; and sample size, reliability and tests of statistical mediation.

Product Details

ISBN-13:	9780761908869
Publisher:	SAGE Publications
Publication date:	03/30/1999
Edition description:	New Edition
Pages:	392
Product dimensions:	6.00(w) x 9.00(h) x 0.87(d)

Table of Contents

On the Performance of Multiple Imputation for Multivariate Data with Small Sample Size - John W Graham and Joseph L Schafer
Maximizing Power in Randomized Designs When N is Small - Anre Venter and Scott E Maxwell
Effect Sizes and Significance Levels in Small-Sample Research - Sharon H Kramer and Robert Rosenthal
Statistical Analysis Using Bootstrapping - Yiu-Fai Yung and Wai Chan
Concepts and Implementation
Meta-Analysis of Single-Case Designs - Scott L Hershberger et al
Exact Permutational Inference for Categorical and Nonparametric Data - Cyrus R Mehta and Nitin R Patel
Tests of an Identity Correlation Structure - Rachel T Fouladi and James H Steiger
Sample Size, Reliability and Tests of Statistical Mediation - Rick H Hoyle and David A Kenny
Pooling Lagged Covariance Structures Based on Short, Multivariate Time Series for Dynamic Factor Analysis - John R Nesselroade and Peter C M Molenaar
Confirmatory Factor Analysis - Herbert W Marsh and Kit-Tai Hau
Strategies for Small Sample Sizes
Small Samples in Structural Equation State Space Modeling - Johan H L Oud, Robert A R G Jansen and Dominique M A Haughton
Structural Equation Modeling Analysis with Small Samples Using Partial Least Squares - Wynne W Chin and Peter R Newsted

Editorial Reviews

Twelve contributions describe and illustrate statistical strategies that are flexible and sophisticated, yet appropriate for analyzing data from small samples of fewer than 150 cases. Many authors use simulations to evaluate the performance of statistical methods based on asymptotic theory in very small samples. Others present strategies for maximizing the yield from small-sample data. The topics include multiple imputation software, hypothesis tests using bootstrapping, confirmatory factor analysis, and structural equation modeling. Annotation c. by Book News, Inc., Portland, Or.

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