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Klappentext 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; when to use latent variable modeling; time-series data from small numbers of individuals; and sample size, reliability and tests of statistical mediation. Zusammenfassung 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; latent variable modeling; and time-series data from small numbers of individuals. Inhaltsverzeichnis 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 ...
