Lagged Effects Modeling
Lagged Effects Modeling is a statistical modeling approach within longitudinal data analysis that specifies temporal dependencies by incorporating delayed influences of predictor variables on outcomes, distinguishing it from contemporaneous models through its explicit representation of effects manifesting at subsequent time points.
287
Publications
16.9K
Citations
1K
Authors
529
Institutions
Publications per year
2017–2026
126
287
Distributed Lag Linear and Non-Linear Models in R: The Package dlnm.
Antonio Gasparrini · PubMed · 2011 · 1.1K citations · Full text
Business, Data Science, Forecasting +16
Taking Account of Time Lags in Causal Models
Harry F. Gollob, Charles S. Reichardt · Child Development · 1987 · 559 citations
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National Institute for Communicable Disease Control and Prevention, China
3 publications · 161 citations
3
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3
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3
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529

Peking University
Beijing, China
7 h-index
22 publications
818 citations
Utrecht University
Utrecht, The Netherlands
7 h-index
17 publications
1.2K citations
University of Pittsburgh
Pittsburgh, United States
6 h-index
16 publications
527 citations

Stockholm University
Stockholm, Sweden
6 h-index
15 publications
1.2K citations
Maastricht University
Maastricht, The Netherlands
6 h-index
9 publications
705 citations
University of Zurich
Zurich, Switzerland
6 h-index
8 publications
104 citations

Pennsylvania State University
State College, United States
5 h-index
17 publications
512 citations
Harvard University
Cambridge, United States
5 h-index
8 publications
2.6K citations
1–8 of 529
9 publications · 769 citations
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Repository · 8 publications · 320 citations
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6 publications · 239 citations
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5 publications · 103 citations
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JFP · 5 publications · 428 citations
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