Small sample size solutions : a guide for applied researchers and practitioners
/ edited by Rens van de Schoot and Milica Miočevic
- 1 online resource (269 pages) : illustrations
- European Association of Methodology series .
Includes bibliographical references and index.
Part I. Bayesian solutions Introduction to Bayesian statistics The role of exchangeability in sequential updating of findings from small studies and the challenges of identifying exchangeable data sets A tutorial on using the WAMBS checklist to avoid the misuse of Bayesian statistics The importance of collaboration in Bayesian analyses with small samples A tutorial on Bayesian penalized regression with shrinkage priors for small sample sizes Part II. n = 1 85 One by one : the design and analysis of replicated randomized single-case experiments Single-case experimental designs in clinical intervention research How to improve the estimation of a specific examinee’s (n ¼ 1) math ability when test data are limited Combining evidence over multiple individual analyses Going multivariate in clinical trial studies : a Bayesian framework for multiple binary outcomes Part III. Complex hypotheses and models An introduction to restriktor : evaluating informative hypotheses for linear models Testing replication with small samples: applications to ANOVA Small sample meta-analyses : exploring heterogeneity using MetaForest Item parcels as indicators : why, when, and how to use them in small sample research Small samples in multilevel modeling Small sample solutions for structural equation modeling SEM with small samples : two-step modeling and factor score regression versus Bayesian estimation with informative priors Important yet unheeded : some small sample issues that are often overlooked