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Estimation of the common risk difference in stratified paired binary data with homogeneous stratum effect
1Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA. Daniel-Zhao@ouhsc.edu
Journal of Biopharmaceutical Statistics
|June 22, 2013
Summary
This study introduces a common risk difference (CRD) for stratified binary data when stratum effects are homogeneous. It provides statistical methods for estimating CRD, offering an alternative to stratum-specific McNemar
Area of Science:
- Biostatistics
- Epidemiology
- Statistical Methods
Background:
- McNemar's test is standard for risk differences in paired binary data.
- Stratified paired binary data analysis requires assessing stratum effect homogeneity.
- A recent test for homogeneous stratum effect (HSE) has been developed.
Purpose of the Study:
- To propose a concept of common risk difference (CRD) for stratified paired binary data.
- To derive point estimators and confidence intervals for CRD when HSE is not rejected.
- To evaluate statistical properties of proposed estimators and intervals through simulations.
Main Methods:
- Development of estimators for common risk difference (CRD).
- Derivation of confidence intervals for CRD.
- Simulation studies to assess performance of estimators and confidence intervals.
- Illustration using a cancer study dataset.
Main Results:
- The study proposes a novel approach for analyzing stratified paired binary data.
- Methods for estimating common risk difference (CRD) and its confidence intervals are derived.
- Simulations provide recommendations for point estimators and confidence intervals with good statistical properties.
Conclusions:
- The proposed common risk difference (CRD) method is suitable for stratified paired binary data when stratum effects are homogeneous.
- The derived estimators and confidence intervals offer a statistically sound approach for such data.
- This work provides valuable tools for risk difference analysis in stratified matched-pair studies.
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