ArticleStatistics in medicine2013
Extending the Peters-Belson approach for assessing disparities to right censored time-to-event outcomes.
Article in Statistics in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- Sex differences in cancer incidence persist across race and ethnicity.Biology of sex differences · 2026Article
- Decomposition of longitudinal disparities: an application to the fetal growth-singletons study.Biostatistics (Oxford, England) · 2025Article
- Sex disparities in the incidence of 21 cancer types: Quantification of the contribution of risk factors.Cancer · 2022Article
- Sex disparities in cancer: An ongoing quest.Cancer · 2022Article
- Racial and Ethnic Disparities in the Time to Dual Incontinence and its Treatment in Older Adults after Nursing Home Admission.Annals of gerontology and geriatric research · 2017Article
- Are there racial-ethnic disparities in time to pressure ulcer development and pressure ulcer treatment in older adults after nursing home admission?Journal of aging and health · 2015Article
- Racial and Ethnic Disparities in Time to Cure of Incontinence Present at Nursing Home Admission.Journal of health disparities research and practice · 2014Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The Peters-Belson (PB) method was developed for quantifying and testing disparities between groups in an outcome by using linear regression to compute group-specific observed and expected outcomes. It has since been extended to generalized linear models for binary and other outcomes and to analyses with probability-based sample weighting. In this work, we extend the PB approach to right-censored survival analysis, including stratification if needed. The extension uses the theory and methods of expected survival on the basis of Cox regression in a reference population. Within the PB framework, among the groups to be compared, one group is chosen as the reference group, and outcomes in that group are modeled as a function of available predictors. By using this fitted model's estimated parameters, and the predictor values for a comparator group, the comparator group's expected outcomes are then calculated and compared, formally with testing and informally with graphics, with their observed outcomes. We derive the extension, show how we applied it in a study of incontinence in nursing home elderly, and discuss issues in implementing it. We used the 'survival' package in the R system to do computations.
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Registered trials
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