Complexity and bias in cross-sectional data with binary disease outcome in observational studies

DOI10.1002/SIM.8812zbMATH Open1546.62794MaRDI QIDQ6627938

Yu-Chen Yang, Mei-Cheng Wang

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

logistic modelsampling biascurrent status databirth-illness-death processstationary disease process

Mathematics Subject Classification ID

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Cites Work

• Alternating event processes during lifetimes: population dynamics and statistical inference
• Analysing bivariate survival data with interval sampling and application to cancer epidemiology
• A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data
• Sampling Bias and Logistic Models
• Nonparametric Estimation from Cross-Sectional Survival Data
• Semiparametric Methods for Response-Selective and Missing Data Problems in Regression
• Quasi-likelihood Estimation in Semiparametric Models
• Age-Specific Incidence and Prevalence: A Statistical Perspective
• Estimation of the probability of an event as a function of several independent variables
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