S4 conference

Post-conference workshops

We will close the conference with a day filled with workshops. Each three-hour workshop discusses one specific solution is great detail including some hands-on exercises. Registration is for one specific workshop and always includes lunch (after or before your workshop) and you can combine a morning workshop with one in the afternoon.

Integrating information beyond data: How to obtain informative priors – Duco Veen and Marthe Egberts

Bayesian estimation with (weakly) informative priors can be a solution for small sample size situations. Naïve use of Bayesian statistics, in contrast, can actually cause harm. In this workshop we show where and how to find additional information to specify (weakly) informative priors for your models. Amongst others, we discuss natural parameter constraints and the…

Bayesian analysis of multiple binary outcomes – Xynthia Kavelaars

This workshop provides a practical introduction to the Bayesian analysis of multiple binary outcomes. Participants will be guided through the steps required to compare data from two groups, using freely available online software. In addition, several design-related topics will be covered, such as the specification of a suitable prior distribution and the selection of an…

Using Multilevel Modeling to Meta-Analyze Single-Case Experimental Design Studies’ Results – Wim Van den Noortgate and Mariola Moeyaert

This workshop introduces the use of multilevel models for meta-analyzing single-subject experimental design (SSED) studies. The course will begin with an overview of multilevel modeling and how the model can be used for SSED meta-analysis of unstandardized data. Next, an overview of how to standardize raw data or effect sizes will be given, and the…

Parceling in small sample sizes – Omolola A. Odejimi

In this workshop we will discuss the benefits of parceling in small sample sizes. Parceling addresses several issues stemming from sources of variance commonly found in item level data. We will talk about how parcels can increase power in small sample sizes, avoid convergence issues by reducing model complexity, produce more reasonable type I error…

Replication Lab – Mariëlle Zondervan-Zwijnenburg

In this workshop we will test whether replication attempts actually replicate the original findings. We will discuss what the replication question actually is, and apply the appropriate replication evaluation tool. Mariëlle Zondervan-Zwijnenburg Utrecht University

Shrinkage priors to fit big models on small samples – Sara van Erp

During this workshop we will discuss shrinkage priors. Shrinkage priors are especially useful in models that are large compared to the amount of data available, for example regression models with more predictors than observations. You will learn when and how to use shrinkage priors and get some hands-on experience using the software program Stan. Sara…

Dangers of Default Priors – Sonja Winter and Sanne Smid

A workshop on the impact of default priors when Bayesian Structural Equation Modeling (BSEM) is used with small samples; how to recognize misbehaving priors; and recommendations on what (not) to do when BSEM is used in small sample contexts. Sanne Smid Utrecht University Sonja Winter University of California, Merced

restriktor: beyond classical null-hypothesis testing – Rebecca Kuiper

Confirmatory approaches, such as the GORIC (an AIC-like criterion), have proven to be more `powerful’ (i.e., render a higher probability of choosing the best hypothesis) than exploratory approaches such as the AIC. In this workshop, we will demonstrate that if you specify your theory and competing theory wisely, you can increase your power substantially. This…

Dealing with heterogeneity in meta-analysis – Caspar van Lissa