Assessing selection bias in regression coefficients estimated from nonprobability samples with applications to genetics and demographic surveys
DOI10.1214/21-AOAS1453zbMath1478.62345arXiv2004.06139OpenAlexW3202550049MaRDI QIDQ2247506
Brady T. West, Rebecca R. Andridge, Philip S. Boonstra, Anita Pandit, Erin B. Ware, Fernanda Alvarado-Leiton, Roderick J. A. Little
Publication date: 17 November 2021
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2004.06139
linear regressionselection biasprobit regressionnonprobability samplesNational Survey of Family Growthpolygenic scores
Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10) Statistical ranking and selection procedures (62F07)
Cites Work
- Inference for nonprobability samples
- A Note About Models for Selectivity Bias
- Inference and missing data
- A class of pattern-mixture models for normal incomplete data
- Statistical Analysis with Missing Data, Third Edition
- Pattern-Mixture Models for Multivariate Incomplete Data
- Bias Reduction in Logistic Regression with Missing Responses When the Missing Data Mechanism is Nonignorable
- Alternative Indicators for the Risk of Non‐response Bias: A Simulation Study
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