Semiparametric group testing regression models

DOI10.1093/BIOMET/ASU007zbMath1334.62070OpenAlexW2113439767MaRDI QIDQ3191467

Dewei Wang, Colin M. Gallagher, K. B. Kulasekera, Christopher S. McMahan

Publication date: 2 October 2014

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/f9e659ac20c519466c9f14dfa7256e342b137e92

zbMATH Keywords

sensitivitysemiparametric regressiongroup testingspecificitylatent datapooled data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)

Related Items (10)

groupTesting: an R package for group testing estimation ⋮ Estimating covariate-adjusted measures of diagnostic accuracy based on pooled biomarker assessments ⋮ Single-index regression for pooled biomarker data ⋮ Regression analysis of misclassified current status data with informative observation times ⋮ Semiparametric probit regression model with misclassified current status data ⋮ Estimation of Conditional Prevalence From Group Testing Data With Missing Covariates ⋮ Determination of varying group sizes for pooling procedure ⋮ Regression analysis of misclassified current status data ⋮ Regression models for group testing: identifiability and asymptotics ⋮ Optimizing pooled testing for estimating the prevalence of multiple diseases

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