Design of Validation Studies for Estimating the Odds Ratio of Exposure–Disease Relationships When Exposure Is Misclassified
From MaRDI portal
Publication:4668330
DOI10.1111/j.0006-341X.1999.01193.xzbMath1059.62658OpenAlexW2009356691WikidataQ73789923 ScholiaQ73789923MaRDI QIDQ4668330
Donna Spiegelman, Christina A. Holcroft
Publication date: 18 April 2005
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.0006-341x.1999.01193.x
Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05) Generalized linear models (logistic models) (62J12)
Related Items (3)
Two-Phase Sampling for Simultaneous Prevalence Estimation and Case Detection ⋮ Efficient estimation of regression parameters from multistage studies with validation of outcome and covariates ⋮ Fitting logistic regression models with contaminated case-control data
Uses Software
Cites Work
- Cost-efficient study designs for relative risk modeling with covariate measurement error
- Designing a logistic regression study using surrogate measures for exposure and outcome
- Logistic analysis in case-control studies under validation sampling
- Precision of double sampling estimators for comparing two probabilities
- Logistic regression for two-stage case-control data
- Fitting Logistic Regression Models in Stratified Case-Control Studies
- Conditional Resampling for Misclassified Multinomial Data with Applications to Sampling Inspection
- Inference and missing data
- The Effects of Misclassification on the Estimation of Relative Risk
- Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data: Extensions and Comparisons
- A mean score method for missing and auxiliary covariate data in regression models
This page was built for publication: Design of Validation Studies for Estimating the Odds Ratio of Exposure–Disease Relationships When Exposure Is Misclassified
