Assessing Discrimination of Risk Prediction Rules in a Clustered Data Setting
DOI10.1007/978-1-4614-8981-8_10zbMath1461.62193OpenAlexW4255746179MaRDI QIDQ4984846
Weiliang Qiu, Bernard Rosner, Mei-Ling Ting Lee
Publication date: 20 April 2021
Published in: Risk Assessment and Evaluation of Predictions (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc3622772
prediction ruleestimate regression coefficientgeneralize estimate equationgeneralize estimate equation modelintegrate discrimination improvement
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)
Cites Work
- Unnamed Item
- Unnamed Item
- The Efficiency of Some Nonparametric Competitors of the $t$-Test
- Power and Sample Size Estimation for the Wilcoxon Rank Sum Test with Application to Comparisons of C Statistics from Alternative Prediction Models
- A Unified Approach to Nonparametric Comparison of Receiver Operating Characteristic Curves for Longitudinal and Clustered Data
- Generalized Estimating Equations for Ordinal Categorical Data: Arbitrary Patterns of Missing Responses and Missingness in a Key Covariate
- Extension of the Rank Sum Test for Clustered Data: Two‐Group Comparisons with Group Membership Defined at the Subunit Level
This page was built for publication: Assessing Discrimination of Risk Prediction Rules in a Clustered Data Setting