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National Institute of Environmental Health Sciences

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Your Environment. Your Health.

Publication Detail

Title: Non-response models for the analysis of non-monotone ignorable missing data.

Authors: Robins, J M; Gill, R D

Published In Stat Med, (1997 Jan 15-Feb 15)

Abstract: We discuss a new class of ignorable non-monotone missing data models-the randomized monotone missingness (RMM) models. We argue that the RMM models represent the most general plausible physical mechanism for generating non-monotone ignorable data. We show that there exists ignorable missing data processes that are not RMM. We argue that it may therefore be inappropriate to analyse non-monotone missing data under the assumption that the missingness mechanism is ignorable, if a statistical test has rejected the hypothesis that the missing data process is RMM representable. We use RMM models to analyse data from a case-control study of the effects of radiation on breast cancer.

PubMed ID: 9004382 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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