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   Articles with "outcome dependent" as a keyword



Optimal allocation in stratified cluster-based outcome-dependent sampling designs.

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recommendations! Published in 2021 at "Statistics in medicine"

DOI: 10.1002/sim.9016

Abstract: In public health research, finite resources often require that decisions be made at the study design stage regarding which individuals to sample for detailed data collection. At the same time, when study units are naturally… read more here.

Keywords: outcome dependent; cluster based; based outcome; allocation ... See more keywords

Model misspecification and robust analysis for outcome‐dependent sampling designs under generalized linear models

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recommendations! Published in 2023 at "Statistics in Medicine"

DOI: 10.1002/sim.9673

Abstract: Outcome‐dependent sampling (ODS) is a commonly used class of sampling designs to increase estimation efficiency in settings where response information (and possibly adjuster covariates) is available, but the exposure is expensive and/or cumbersome to collect.… read more here.

Keywords: likelihood; dependent sampling; analysis; phase ... See more keywords

The effects of missing data due to study dropout on longitudinal analysis inference using outcome-dependent sampling.

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recommendations! Published in 2025 at "International journal of epidemiology"

DOI: 10.1093/ije/dyaf150

Abstract: BACKGROUND Existing longitudinal cohort study data and associated biospecimen libraries provide abundant opportunities to efficiently examine new hypotheses through retrospective specimen testing. Outcome-dependent sampling (ODS) methods offer a powerful alternative to random sampling when testing… read more here.

Keywords: mar; random; mnar; dependent sampling ... See more keywords

Improving estimation efficiency for two-phase, outcome-dependent sampling studies

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recommendations! Published in 2022 at "Electronic Journal of Statistics"

DOI: 10.1214/23-ejs2124

Abstract: Two-phase outcome dependent sampling (ODS) is widely used in many fields, especially when certain covariates are expensive and/or difficult to measure. For two-phase ODS, the conditional maximum likelihood (CML) method is very attractive because it… read more here.

Keywords: phase outcome; dependent sampling; outcome dependent; phase ... See more keywords