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Masking Unmasked in the Proportional Hazards Model
Author(s) -
Wei Wen Hsiang,
Kosorok Michael R.
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.0991.x
Subject(s) - pairwise comparison , proportional hazards model , inference , computer science , statistical model , statistics , econometrics , statistical inference , masking (illustration) , hazard , data mining , mathematics , artificial intelligence , biology , art , ecology , visual arts
Summary. Influence measures based on the pairwise deletion approach and the differentiation approach are developed for unmasking observations masked by other observations in the proportional hazards model. These influential observations might have substantial impact on statistical inference and might provide important information for model adequacy. One numerical example based on real data is presented and discussed.