Binary Longitudinal Models is a statistical modeling framework that belongs to the class of generalized linear mixed models and is specifically characterized by its application to repeated binary outcome measures over time, incorporating within-subject correlation and time-varying covariates to estimate population-averaged or subject-specific effects in longitudinal data.
143
Publications
10.1K
Citations
354
Authors
200
Institutions
Publications per year
2017–2026
19
Publications
143
Efficient Screening of Nonnormal Regression Models
Jerald F. Lawless, K. Singhal · Biometrics · 1978 · 242 citations
1–5 of 143
Authors
354
- GM
7
h-index
- GM
5
h-index
- SL
5
h-index
- NM
4
h-index
- KK
4
h-index
1–5 of 354
Institutions
200
Wake Forest University
Winston-Salem, United States
7 h-index
12 publications
438 citations
Johns Hopkins University
Baltimore, United States
7 h-index
14 publications
610 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
6 h-index
6 publications
470 citations
Harvard University
Cambridge, United States
6 h-index
9 publications
811 citations
University of Washington
Seattle, United States
6 h-index
7 publications
471 citations
Cancer Research And Biostatistics
Seattle, United States
5 h-index
10 publications
816 citations
University of Waterloo
Waterloo, Canada
5 h-index
8 publications
403 citations
National Cancer Institute
Bethesda, United States
4 h-index
4 publications
202 citations
1–8 of 200
Venues
- Statistics in Medicine
18 publications · 810 citations
15
h-index
- Biometrics
16 publications · 1.1K citations
14
h-index
- Journal of the American Statistical Association
10 publications · 431 citations
10
h-index
- Biometrika
10 publications · 917 citations
10
h-index
- Computational Statistics & Data Analysis
CSDA · 6 publications · 180 citations
6
h-index
1–5