papers

Publications (24)

cs.LG2024

Combining the Strengths of Dutch Survey and Register Data in a Data Challenge to Predict Fertility (PreFer)

Elizaveta Sivak, Paulina Pankowska, Adrienne Mendrik +8

The social sciences have produced an impressive body of research on determinants of fertility outcomes, or whether and when people have children. However, the strength of these det…

stat.ME2023

A Bayesian actor-oriented multilevel relational event model with hypothesis testing procedures

Fabio Vieira, Roger Leenders, Daniel McFarland +1

Relational event network data are becoming increasingly available. Consequently, statistical models for such data have also surfaced. These models mainly focus on the analysis of s…

math.ST2017

On the Ubiquity of Information Inconsistency for Conjugate Priors

Joris Mulder, James O. Berger, Víctor Peña +1

Informally, "Information Inconsistency" is the property that has been observed in many Bayesian hypothesis testing and model selection procedures whereby the Bayesian conclusion do…

stat.ME2021

Bayesian testing of linear versus nonlinear effects using Gaussian process priors

Joris Mulder

A Bayes factor is proposed for testing whether the effect of a key predictor variable on the dependent variable is linear or nonlinear, possibly while controlling for certain covar…

stat.ME2022

Separating the Wheat from the Chaff: Bayesian Regularization in Dynamic Social Networks

Diana Karimova, Joris Mulder, Roger Th. A. J. Leenders

In recent years there has been an increasing interest in the use of relational event models for dynamic social network analysis. The basis of these models is the concept of an "eve…

stat.ME2023

Bayesian Testing of Scientific Expectations Under Exponential Random Graph Models

Joris Mulder, Nial Friel, Philip Leifeld

The exponential random graph (ERGM) model is a commonly used statistical framework for studying the determinants of tie formations from social network data. To test scientific theo…

stat.ME2019

BIC extensions for order-constrained model selection

Joris Mulder, Adrian E. Raftery

The Schwarz or Bayesian information criterion (BIC) is one of the most widely used tools for model comparison in social science research. The BIC however is not suitable for evalua…

stat.ME2023

Bayesian multilevel multivariate logistic regression for superiority decision-making under observable treatment heterogeneity

Xynthia Kavelaars, Joris Mulder, Maurits Kaptein

In medical, social, and behavioral research we often encounter datasets with a multilevel structure and multiple correlated dependent variables. These data are frequently collected…

stat.ME2024

To Vary or Not To Vary: A Simple Empirical Bayes Factor for Testing Variance Components

Fabio Vieira, Hongwei Zhao, Joris Mulder

Random effects are a flexible addition to statistical models to capture structural heterogeneity in the data, such as spatial dependencies, individual differences, temporal depende…

stat.ME2024

A Latent Variable Model for Relational Events with Multiple Receivers

Joris Mulder, Peter D. Hoff

Directional relational event data, such as email data, often contain unicast messages (i.e., messages of one sender towards one receiver) and multicast messages (i.e., messages of…

stat.ME2019

Simple Bayesian testing of scientific expectations in linear regression models

Joris Mulder, Anton Olsson-Collentine

Scientific theories can often be formulated using equality and order constraints on the relative effects in a linear regression model. For example, it may be expected that the effe…

stat.ME2019

Bayes factor testing of equality and order constraints on measures of association in social research

Joris Mulder, John P. T. M. Gelissen

Measures of association play a central role in the social sciences to quantify the strength of a linear relationship between the variables of interest. In many applications researc…

stat.ME2018

The Lazy Bootstrap. A Fast Resampling Method for Evaluating Latent Class Model Fit

Geert H. van Kollenburg, Joris Mulder, Jeroen K. Vermunt

The latent class model is a powerful unsupervised clustering algorithm for categorical data. Many statistics exist to test the fit of the latent class model. However, traditional m…

stat.ME2025

Bayes Factor Hypothesis Testing in Meta-Analyses: Practical Advantages and Methodological Considerations

Joris Mulder, Robbie C. M. van Aert

Bayesian hypothesis testing via Bayes factors offers a principled alternative to classical p-value methods in meta-analysis, particularly suited to its cumulative and sequential na…

stat.CO2026

Learning Nonlinear Dynamics: Improving the Estimation Efficiency and Reliability of Gaussian Process State-Space Models

Jan I. Failenschmid, Leonie V. D. E. Vogelsmeier, Joris Mulder +1

Understanding dynamic systems is a central goal in many scientific disciplines. State-space models provide a general framework for studying latent dynamic systems based on indirect…

cs.SI2025

Simulating Relational Event Histories: Why and How

Rumana Lakdawala, Joris Mulder, Roger Leenders

Many important social phenomena are characterized by repeated interactions among individuals over time such as email exchanges in an organization or face-to-face interactions in a…

stat.ME2021

A Bayesian semi-parametric approach for modeling memory decay in dynamic social networks

Giuseppe Arena, Joris Mulder, Roger Th. A. J. Leenders

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the quantity…

stat.CO2019

BFpack: Flexible Bayes Factor Testing of Scientific Theories in R

Joris Mulder, Xin Gu, Anton Olsson-Collentine +10

There has been a tremendous methodological development of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to…

stat.ME2024

Bayesian multivariate logistic regression for superiority and inferiority decision-making under observable treatment heterogeneity

Xynthia Kavelaars, Joris Mulder, Maurits Kaptein

The effects of treatments may differ between persons with different characteristics. Addressing such treatment heterogeneity is crucial to investigate whether patients with specifi…

stat.ME2024

Comment on "Safe Testing" by Grünwald, de Heide, and Koolen

Joris Mulder

This comment briefly reflects on "Safe Testing" by Grüwald et al. (2024). The safety of fractional Bayes factors (O'Hagan, 1995) is illustrated and compared to (safe) Bayes factor…

stat.ME2025

Comment on García-Donato et al. (2025) "Model uncertainty and missing data: An objective Bayesian perspective"

Joris Mulder

Garcia-Donato et al. (2025) present a methodology for handling missing data in a model selection problem using an objective Bayesian approach. The current comment discusses an alte…

cs.SI2025

Not All Bonds Are Created Equal: Dyadic Latent Class Models for Relational Event Data

Rumana Lakdawala, Roger Leenders, Joris Mulder

Dynamic social networks can be conceptualized as sequences of dyadic interactions between individuals over time. The relational event model has been the workhorse to analyze such i…

stat.ME2025

To Vary or Not To Vary: A Flexible Empirical Bayes Factor for Testing Variance Components

Fabio Vieira, Hongwei Zhao, Joris Mulder

Random effects are the gold standard for capturing structural heterogeneity in data, such as spatial dependencies, individual differences, or temporal dependencies. However, testin…

cs.SI2026

Modelling Interaction Duration in Relational Event Models

Rumana Lakdawala, Roger Leenders, Peter Ejbye-Ernst +1

The study of relational events, which are interactions occurring between actors over time, has gained significant traction recently. Traditional relational event models typically f…