Statistical implication analysis: a novel approach to understand the reciprocal relationships between outcomes in early psychosis
The concept of implication is an interesting way of evaluating dependencies between outcomes as it allows us to overcome the tendency to presume symmetrical relationships between them. We argue that a better understanding of reciprocal dependencies within psychopathology can provide an impetus to tailormade treatments and SIA is a useful tool to address this issue in cross-sectional designs.
Authors
- Philippe Conus (ORCID: https://orcid.org/0000-0002-5832-1910)
- Luis Alameda (ORCID: https://orcid.org/0000-0002-8621-2885)
- Vincent Bonnarel
- Philippe Golay (ORCID: https://orcid.org/0000-0002-2273-6241)
- Nadir Mebdouhi
- Lilith Abrahamyan Empson (ORCID: https://orcid.org/0000-0002-0495-2979)
- Caroline Conchon
Institutions
- King's College London (GB)
- Centro de Investigación Biomédica en Red de Salud Mental (ES)
- Institute of Social Sciences (RS)
- Instituto de Biomedicina de Sevilla (ES)
- Institute of Social and Preventive Medicine (CH)
- Czech Academy of Sciences, Institute of Psychology (CZ)
- Hospital Universitario Virgen del Rocío (ES)
- University of Lausanne (CH)
Publication Details
- Journal
- Psychological Medicine
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1017/s0033291724001430
- Primary Topic
- Schizophrenia research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung