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Statistical Strategies for Small Sample Research
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Statistical Strategies for Small Sample Research

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May 1999 | 392 pages | SAGE Publications, Inc
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.
John W Graham and Joseph L Schafer
On the Performance of Multiple Imputation for Multivariate Data with Small Sample Size
Anre Venter and Scott E Maxwell
Maximizing Power in Randomized Designs When N is Small
Sharon H Kramer and Robert Rosenthal
Effect Sizes and Significance Levels in Small-Sample Research
Yiu-Fai Yung and Wai Chan
Statistical Analysis Using Bootstrapping
Concepts and Implementation

 
Scott L Hershberger et al
Meta-Analysis of Single-Case Designs
Cyrus R Mehta and Nitin R Patel
Exact Permutational Inference for Categorical and Nonparametric Data
Rachel T Fouladi and James H Steiger
Tests of an Identity Correlation Structure
Rick H Hoyle and David A Kenny
Sample Size, Reliability and Tests of Statistical Mediation
John R Nesselroade and Peter C M Molenaar
Pooling Lagged Covariance Structures Based on Short, Multivariate Time Series for Dynamic Factor Analysis
Herbert W Marsh and Kit-Tai Hau
Confirmatory Factor Analysis
Strategies for Small Sample Sizes

 
Johan H L Oud, Robert A R G Jansen and Dominique M A Haughton
Small Samples in Structural Equation State Space Modeling
Wynne W Chin and Peter R Newsted
Structural Equation Modeling Analysis with Small Samples Using Partial Least Squares

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