Mixed-effects Dose-response Models
Mixed-Effects Dose-Response Models is a statistical modeling framework that belongs to the class of dose-response models by characterizing the relationship between dose levels and response outcomes, distinguished by its incorporation of both fixed effects to capture population-level trends and random effects to account for within-subject correlations and inter-individual variability in longitudinal data.
21
Publications
2.4K
Citations
66
Authors
39
Institutions
Publications per year
2017–2026
3
21
Multilevel models Improve precision and Speed of IC <sub>50</sub> Estimates
Daniël J. Vis, Lorenzo Bombardelli, Howard Lightfoot et al. · Pharmacogenomics · 2016 · 80 citations · Full text
1–5 of 21
66
4
h-index
2
h-index
2
h-index
1
h-index
1
h-index
1–5 of 66
39

Karolinska Institutet
Stockholm, Sweden
4 h-index
10 publications
4.1K citations
Los Angeles County Department of Public Health
Los Angeles, United States
1 h-index
1 publications
47 citations
R&G Associates
Berwick-Upon-Tweed, United Kingdom
1 h-index
1 publications
25 citations
Harvard University
Cambridge, United States
1 h-index
1 publications
350 citations
Oncode Institute
Utrecht, Netherlands
1 h-index
3 publications
240 citations

Istituto Nazionale di Statistica
Rome, Italy
1 h-index
2 publications
166 citations
Center for Personalized Cancer Treatment
Rotterdam, Netherlands
1 h-index
2 publications
160 citations
Case Western Reserve University
Cleveland, United States
1 h-index
1 publications
47 citations
1–8 of 39
3 publications · 1.4K citations
3
h-index
1 publications · 15 citations
1
h-index
AAPSJ · 1 publications · 65 citations
1
h-index
1 publications · 47 citations
1
h-index
1 publications · 80 citations
1
h-index
1–5