Sensitivity analysis in psychological and medical research [data]

DOI

This dataset contains all data and R code necessary to follow the tutorial "Sensitivity analysis in psychological and medical research: A tutorial using multiple imputation in a longitudinal case study".

People interested in learning sensitivity analysis with multiple imputation are free to download the data and R code and follow along.

MIcrosoft Excel, 2019

R Statistical Software, 4.4.1

Data was collected within a project of medical education. Medical students could attend a six-week, once a week, trainings seminar aimed at reducing test anxiety. Training started five weeks prior to the first exam. Training was based on Kaluza (2018). Training included learning strategies, time management strategies, stress prevention and relaxation. In addition, students were encouraged to talk about their stressors, with the aim to improve group cohesion. The projects hypothesis was that an increase in group cohesion leads to a decrease in test anxiety.

Identifier
DOI https://doi.org/10.11588/DATA/KSUCME
Metadata Access https://heidata.uni-heidelberg.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.11588/DATA/KSUCME
Provenance
Creator Dönnhoff, Ivo ORCID logo; Bergner, Thilo; Riedel, Caroline; Friederich, Hans-Christoph ORCID logo; Bugaj, Till J. ORCID logo
Publisher heiDATA
Contributor Dönnhoff, Ivo; Bergner, Thilo; Riedel, Caroline; Friederich, Hans-Christoph; Bugaj, Till J.; heiDATA: Heidelberg Research Data Repository
Publication Year 2025
Rights CC BY-NC 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by-nc/4.0
OpenAccess true
Contact Dönnhoff, Ivo (Heidelberg University Hospital)
Representation
Resource Type Psychometric Questionnaire Data; Dataset
Format application/zip
Size 9564943; 42825584; 1532408; 14326
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Mathematics; Medicine; Natural Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences