ArticleBiostatistics (Oxford, England)2014
A conditional predictive p-value to compare a multinomial with an overdispersed multinomial in the analysis of T-cell populations.
Article in Biostatistics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- SURROGATE SELECTION OVERSAMPLES EXPANDED T CELL CLONOTYPES.The annals of applied statistics · 2025Article
- Enrichment of melanoma-associated T cells in 6-thioguanine-resistant T cells from metastatic melanoma patients.Melanoma research · 2020Article
- Molecular characterization of hypoxanthine guanine phosphoribosyltransferase mutant T cells in human blood: The concept of surrogate selection for immunologically relevant cells.Mutation research. Reviews in mutation researchReview
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Authors and funding
5 authors.
Funding
Abstract
Immunological experiments that record primary molecular sequences of T-cell receptors produce moderate to high-dimensional categorical data, some of which may be subject to extra-multinomial variation caused by technical constraints of cell-based assays. Motivated by such experiments in melanoma research, we develop a statistical procedure for testing the equality of two discrete populations, where one population delivers multinomial data and the other is subject to a specific form of overdispersion. The procedure computes a conditional-predictive p-value by splitting the data set into two, obtaining a predictive distribution for one piece given the other, and using the observed predictive ordinate to generate a p-value. The procedure has a simple interpretation, requires fewer modeling assumptions than would be required of a fully Bayesian analysis, and has reasonable operating characteristics as evidenced empirically and by asymptotic analysis.
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Registered trials
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