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Multilevel Modeling/Random Effects Modeling

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A Practical Guide to Specifying Random Effects in Longitudinal Dyadic Multilevel Modeling

  • Kareena S. del Rosario
  • Tessa V. West

Abstract

Analyzing over-time dyadic data can be challenging, particularly when using multilevel models with complex random-effect structures. In this tutorial, we discuss the best practices of model specification for longitudinal dyadic multilevel modeling, ...
Open AccessResearch articleFirst published Sep 9, 2025
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Side Effects of Experience-Sampling Protocols: A Systematic Analysis of How They Affect Data Quality, Data Quantity, and Bias in Study Results

  • Thomas Reiter
  • Sophia Sakel
  • Julian Scharbert
  • Julian ter Horst
  • Maarten van Zalk
  • Mitja Back
  • Markus Bühner
  • Ramona Schoedel

Abstract

In studies using the increasingly popular experience-sampling method (ESM), design decisions are often guided by theoretical or practical considerations. Yet limited empirical evidence exists on how these choices affect data quantity (e.g., response ...
Open AccessResearch articleFirst published Jul 29, 2025
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A Tutorial on Tailored Simulation-Based Sample-Size Planning for Experimental Designs With Generalized Linear Mixed Models

  • Florian Pargent
  • Timo K. Koch
  • Anne-Kathrin Kleine
  • Eva Lermer
  • Susanne Gaube

Abstract

When planning experimental research, determining an appropriate sample size and using suitable statistical models are crucial for robust and informative results. The recent replication crisis underlines the need for more rigorous statistical methodology ...
Open AccessResearch articleFirst published Dec 13, 2024
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Capturing the Social Life of a Person by Integrating Experience-Sampling Methodology and Personal-Social-Network Assessments

  • Marie Stadel
  • Laura F. Bringmann
  • Gert Stulp
  • Timon Elmer
  • Stijn Verdonck
  • Merijn Mestdagh
  • Marijtje A. J. van Duijn

Abstract

The daily social life of a person can be captured with different methodologies. Two methods that are especially promising are personal-social-network (PSN) data collection and experience-sampling methodology (ESM). Whereas PSN data collections ask ...
Open AccessResearch articleFirst published Apr 15, 2024
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Reliability and Feasibility of Linear Mixed Models in Fully Crossed Experimental Designs

  • Michele Scandola
  • Emmanuele Tidoni

Abstract

The use of linear mixed models (LMMs) is increasing in psychology and neuroscience research In this article, we focus on the implementation of LMMs in fully crossed experimental designs. A key aspect of LMMs is choosing a random-effects structure ...
Open AccessResearch articleFirst published Feb 9, 2024
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Beyond Random Effects: When Small-Study Findings Are More Heterogeneous

  • T. D. Stanley
  • Hristos Doucouliagos
  • John P. A. Ioannidis

Abstract

New meta-regression methods are introduced that identify whether the magnitude of heterogeneity across study findings is correlated with their standard errors. Evidence from dozens of meta-analyses finds robust evidence of this correlation and that small-...
Open AccessResearch articleFirst published Oct 26, 2022
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An Introduction to Linear Mixed-Effects Modeling in R

  • Violet A. Brown

Abstract

This Tutorial serves as both an approachable theoretical introduction to mixed-effects modeling and a practical introduction to how to implement mixed-effects models in R. The intended audience is researchers who have some basic statistical knowledge, but ...
Open AccessResearch articleFirst published Mar 25, 2021
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Making the Black Box Transparent: A Template and Tutorial for Registration of Studies Using Experience-Sampling Methods

  • Olivia J. Kirtley
  • Ginette Lafit
  • Robin Achterhof
  • Anu P. Hiekkaranta
  • Inez Myin-Germeys

Abstract

A growing interest in understanding complex and dynamic psychological processes as they occur in everyday life has led to an increase in studies using ambulatory assessment techniques, including the experience-sampling method (ESM) and ecological ...
Open AccessResearch articleFirst published Mar 2, 2021
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Enriching Meta-Analytic Models of Summary Data: A Thought Experiment and Case Study

  • Blakeley B. McShane
  • Ulf Böckenholt

Abstract

Meta-analysis typically involves the analysis of summary data (e.g., means, standard deviations, and sample sizes) from a set of studies via a statistical model that is a special case of a hierarchical (or multilevel) model. Unfortunately, the common ...
Free accessResearch articleFirst published Nov 26, 2019
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Models to Examine the Validity of Cluster-Level Factor Structure Using Individual-Level Data

  • Laura M. Stapleton
  • Tessa L. Johnson

Abstract

When researchers model multilevel data, often a shared construct of interest is measured by individual-level observations, for example, students’ responses regarding how engaging their instructor’s teaching style is. In such cases, the construct of ...
Free accessResearch articleFirst published Aug 21, 2019
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