Rick H. Hoyle

Statistical Strategies for Small Sample Research

Herausgeber: Hoyle, Rick H.

• Broschiertes Buch

Produktbeschreibung

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.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Sage Publications
• Seitenzahl: 392
• Erscheinungstermin: 30. März 1999
• Englisch
• Abmessung: 229mm x 152mm x 24mm
• Gewicht: 635g
• ISBN-13: 9780761908869
• ISBN-10: 0761908862
• Artikelnr.: 21996427

Inhaltsangabe

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