## Statistical Strategies for Small Sample ResearchThis 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. |

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### Contents

On the Performance of Multiple Imputation | 1 |

Maximizing Power in Randomized Designs | 31 |

Maximizing Power in Randomized Designs | 37 |

An Introduction | 60 |

Effect Sizes and Significance Levels | 63 |

Effect Sizes Across Studies | 70 |

References | 76 |

MetaAnalysis of SingleCase Designs | 107 |

Discussion and Conclusions | 245 |

Strategies | 251 |

Small Samples in Structural Equation State | 285 |

Structural Equation Modeling Analysis with | 307 |

The Standard Partial Least Squares Algorithm | 315 |

Formal Specification of the Partial Least | 321 |

The Issue | 328 |

Summary | 335 |

Exact Permutational Inference for Categorical | 133 |

Tests of an Identity Correlation Structure | 167 |

Sample Size Reliability and Tests | 195 |

Pooling Lagged Covariance Structures Based | 223 |

Dynamic Factor Analysis of Pooled Lagged | 234 |

343 | |

349 | |

About the Contributors | 361 |

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### Common terms and phrases

6-weights algorithm ANCOVA assessment asymptotic behavioral between-subjects design bias bootstrap CBSEM coefficients collinearity computed confidence intervals contingency tables counternull data augmentation data set effect size effect sizes equal-loading strategy evaluate exact example factor analysis factor loadings Fouladi FSSL increasing independent variable Journal lagged latent variable model least squares likelihood linear LISREL Low reliability matrix maximum likelihood mean mediator meta-analysis methods missing data missing values missingness Moderate reliability multiple imputation multivariate nominal alpha NORM normal null hypothesis number of indicators observed obtained parameter estimates partial least squares path performance phase population value posttest prediction predictor pretest pretest-posttest design procedure Psychology r x c random regression replicability RMAX Rosenthal sample size sample sizes sampling distribution scores significant single-case small sample standard errors statistical power structural equation modeling subjects test statistic tion true model Type I error variance within-subjects design