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• W2736760148 abstract "Studies about the genetic basis for disease are routinely conducted through family studies under response-dependent sampling in which affected individuals called probands are sampled from a disease registry, and their respective family members (non-probands) are recruited for study. The extent to which the dependence in some feature of the disease process (e.g., presence, age of onset, severity) varies according to the kinship of individuals reflects the evidence of a genetic cause for disease. When the probands are selected from a disease registry, it is common for them to provide quite detailed information regarding their disease history, but non-probands often simply provide their disease status at the time of contact. We develop conditional second-order estimating equations for studying the nature and extent of within-family dependence which recognizes the biased sampling scheme employed in family studies and the current status data provided by the non-probands. Simulation studies are carried out to evaluate the finite sample performance of different estimating functions and to quantify the empirical relative efficiency of the various methods. Sensitivity to model misspecification is also explored. An application to a motivating psoriatic arthritis family study is given for illustration." @default.
• W2736760148 created "2017-07-31" @default.
• W2736760148 creator A5054553011 @default.
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• W2736760148 date "2017-07-24" @default.
• W2736760148 modified "2023-10-03" @default.
• W2736760148 title "Second-Order Estimating Equations for Clustered Current Status Data from Family Studies Using Response-Dependent Sampling" @default.
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• W2736760148 doi "https://doi.org/10.1007/s12561-017-9201-4" @default.
• W2736760148 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6097126" @default.
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• W2736760148 hasPublicationYear "2017" @default.
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