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