Madlen Hoffstadt
Biographic Data
| ID | 4607001 |
|---|---|
| NAME | Madlen Hoffstadt |
| GIVEN NAMES | Madlen |
| FAMILY NAME | Hoffstadt |
| SIGNATURE | HOFFSTADT M |
| AFFILIATIONS | Department of Psychology University of Amsterdam Amsterdam The Netherlands |
| ORCID | 0009-0001-3534-4335 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
ReMoDe – Recursive modality detection in distributions of ordinal data
The detection of the number of modes in distributions of ordinal data is relevant for applied researchers across disciplines, from uncovering polarization to detecting incidence groups in clinical symptom scales. Yet, established modality detection methods are either purely descriptive or not developed for ordinal data. In the present paper, we attempt to fill this gap by proposing a recursive modality detection method (ReMoDe) which detects mode…
Involvement as a Polarizing Factor?—A Comprehensive Multi‐Method Analysis across Representative Datasets
Complex system models of attitudes, such as the Hierarchical Ising Opinion Model (HIOM), suggest that a person's involvement in an attitude object could be linked to attitude extremity and polarization. Despite its potential to integrate various theories of attitude change and despite the implications it could hold for attitude research, this assumption has not yet been studied systematically. We investigate the role of involvement in five large‐…
No prominent works on this page.
Involvement as a Polarizing Factor?—A Comprehensive Multi‐Method Analysis across Representative Datasets
Complex system models of attitudes, such as the Hierarchical Ising Opinion Model (HIOM), suggest that a person's involvement in an attitude object could be linked to attitude extremity and polarization. Despite its potential to integrate various theories of attitude change and despite the implications it could hold for attitude research, this assumption has not yet been studied systematically. We investigate the role of involvement in five large‐…
ReMoDe – Recursive modality detection in distributions of ordinal data
The detection of the number of modes in distributions of ordinal data is relevant for applied researchers across disciplines, from uncovering polarization to detecting incidence groups in clinical symptom scales. Yet, established modality detection methods are either purely descriptive or not developed for ordinal data. In the present paper, we attempt to fill this gap by proposing a recursive modality detection method (ReMoDe) which detects mode…
Benchmark (surveying) (1 work) · Clinical Reasoning and Diagnostic Skills (1 work) · Complex Network Analysis Techniques (1 work) · Computer Science (1 work) · Factor (programming language) (1 work) · Imbalanced Data Classification Techniques (1 work) · Modality (human–computer interaction) (1 work) · Opinion Dynamics and Social Influence (1 work) · Ordinal data (1 work) · Ordinal Scale (1 work)