Results 191 to 200 of about 852,757 (260)

Comparing methods for glomerular filtration rate estimation. [PDF]

J Clin Transl Sci
Zhu X, Shafi T, Norris KC, Simino J, Shrestha S, Mosley TH, Griswold ME, Lirette ST.   +7 more
europepmc   +1 more source

Acute Kidney Injury Diagnostic Accuracy and Implications of Different Baseline Creatinine Equations. [PDF]

Kidney Int Rep
Bjornstad EC, Acharjee MK, Rahman AKMF, Zappitelli M, Basu RK, Schwartz GJ, Goldstein SL, Braun C, Askenazi D.   +8 more
europepmc   +1 more source

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Akaike's Information Criterion in Generalized Estimating Equations

Biometrics, 2001
Summary.Correlated response data are common in biomedical studies. Regression analysis based on the generalized estimating equations (GEE) is an increasingly important method for such data. However, there seem to be few model‐selection criteria available in GEE.
W. Pan
semanticscholar   +4 more sources

Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations

Journal of educational and behavioral statistics, 2021
The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach.
Francis L. Huang
semanticscholar   +1 more source

Stagewise generalized estimating equations with grouped variables

Biometrics, 2017
SummaryForward stagewise estimation is a revived slow-brewing approach for model building that is particularly attractive in dealing with complex data structures for both its computational efficiency and its intrinsic connections with penalized estimation.
Gregory Vaughan, R. Aseltine, Kun Chen, Jun Yan   +3 more
semanticscholar   +4 more sources

Maintaining the validity of inference in small‐sample stepped wedge cluster randomized trials with binary outcomes when using generalized estimating equations

Statistics in Medicine, 2020
Stepped wedge cluster trials are an increasingly popular alternative to traditional parallel cluster randomized trials. Such trials often utilize a small number of clusters and numerous time intervals, and these components must be considered when ...
Whitney P Ford, P. Westgate
semanticscholar   +1 more source

Generalized Estimating Equations Logistic Regression

, 2015
Many fields of study use longitudinal datasets, which usually consist of repeated measurements of a response variable, often accompanied by a set of covariates for each of the subjects/units. However, longitudinal datasets are problematic because they inherently show correlation due to a subject’s repeated set of measurements.
Jeffrey R. Wilson, K. Lorenz
semanticscholar   +3 more sources

Generalized Estimating Equations

2002
Correlated datasets develop when multiple observations are collected from a sampling unit (e.g., repeated measures of a bank over time, or hormone levels in a breast cancer patient over time), or from clustered data where observations are grouped based on a shared characteristic (e.g., observations on different banks grouped by zip code, or on cancer ...
Joseph Hilbe, James W. Hardin
openaire   +5 more sources

Miscellanea. Multiple roots in general estimating equations

Biometrika, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
C. C. Heyde, Richard M. Morton
openaire   +2 more sources

Practical issues in using generalized estimating equations for inference on transitions in longitudinal data: What is being estimated?

Statistics in Medicine, 2018
Generalized estimating equations (GEEs) are commonly used to estimate transition models. When the Markov assumption does not hold but first‐order transition probabilities are still of interest, the transition inference is sensitive to the choice of ...
Joe Bible, P. Albert, B. Simons-Morton, Danping Liu   +3 more
semanticscholar   +1 more source