hierarchical models

Between-case standardized mean differences: Flexible methods for single-case designs

Single-case designs (SCDs) are a class of research methods for evaluating the effects of academic and behavioral interventions in educational and clinical settings. Although visual analysis is typically the first and main method for primary analysis …

Variance component estimates in meta-analysis with mis-specified sampling correlation

\[ \def\Pr{{\text{Pr}}} \def\E{{\text{E}}} \def\Var{{\text{Var}}} \def\Cov{{\text{Cov}}} \] In a recent paper with Beth Tipton, we proposed new working models for meta-analyses involving dependent effect sizes. The central idea of our approach is to use a working model that captures the main features of the effect size data, such as by allowing for both between- and within-study heterogeneity in the true effect sizes (rather than only between-study heterogeneity).

The Woodbury identity

As in many parts of life, statistics is full of little bits of knowledge that are useful if you happen to know them, but which hardly anybody ever bothers to mention.


Information Matrices for 'lmeStruct' and 'glsStruct' Objects

Bug in nlme::lme with fixed sigma and REML estimation

About one year ago, the nlme package introduced a feature that allowed the user to specify a fixed value for the residual variance in linear mixed effect models fitted with lme().

Bug in nlme::getVarCov

I have recently been working to ensure that my clubSandwich package works correctly on fitted lme and gls models from the nlme package, which is one of the main R packages for fitting hierarchical linear models.


Between-case SMD for single-case designs

Design-comparable effect sizes in multiple baseline designs: A general modeling framework

In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction …

New article: Design-comparable effect sizes in multiple baseline designs: A general modeling framework

My article with Larry Hedges and Will Shadish, titled “Design-comparable effect sizes in multiple baseline designs: A general modeling framework” has been accepted at Journal of Educational and Behavioral Statistics.

Analyzing single-case designs: d, G, hierarchical models, Bayesian estimators, generalized additive models, and the hopes and fears of researchers about analyses

New approaches to the analyses of single-case designs are proliferating, which some single-case design researchers welcome and others view with skepticism. In this chapter we describe some of the analyses that we have been exploring, all of which can …