Predicting dropout in intensive longitudinal data: Extending the joint model for autocorrelated data.

Authors

Felix Petersen (ORCID: https://orcid.org/0000-0002-4913-8532)
Laura Francina Bringmann (ORCID: https://orcid.org/0000-0002-8091-9935)
Dimitris Rizopoulos (ORCID: https://orcid.org/0000-0001-9397-0900)

Institutions

University of Groningen (NL)

Publication Details

Journal: Psychological Assessment
Published: 2025-10-01
DOI: https://doi.org/10.1037/pas0001397
Primary Topic: Statistical Methods and Inference
Type: article
Field-Weighted Citation Impact: 0.00

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article

Predicting dropout in intensive longitudinal data: Extending the joint model for autocorrelated data.

Felix Petersen, Laura Francina Bringmann, Dimitris Rizopoulos

Oct 1, 2025

Psychological Assessment

Statistical Methods and Inference

article

Predicting dropout in intensive longitudinal data: Extending the joint model for autocorrelated data.

Felix Petersen, Laura Francina Bringmann, Dimitris Rizopoulos

October 1, 2025article en

Abstract

No abstract available for this paper.

Psychological AssessmentVol. 37(10)

University of Groningen (NL)

Openalex Percentile: Top 72%

Statistical Methods and Inference

DOI Open Access PDF OpenAlex

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Predicting dropout in intensive longitudinal data: Extending the joint model for autocorrelated data. — Felix Petersen, Laura Francina Bringmann, et al. · Psychological Assessment (2025) | TGRS Research Map | TGRS