TY  - JOUR
PY  - 1997//
TI  - Non-response models for the analysis of non-monotone ignorable missing data
JO  - Statistics in Medicine
A1  - Robins, J. M.
A1  - Gill, R. D.
SP  - 39
EP  - 56
VL  - 16
IS  - 1-3
N2  - 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.<p /> <p>Language: en</p>
LA  - en
SN  - 0277-6715
UR  - http://dx.doi.org/
ID  - ref1
ER  -