Pattern-mixture models for analyzing normal outcome data with proxy respondents
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Statistical analysis with missing exposure data measured by proxy respondents: a misclassification problem within a missing-data problem.Comparing reports from hip-fracture patients and their proxies: implications on evaluating sex differences in disability and depressive symptoms.Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.
P2860
Pattern-mixture models for analyzing normal outcome data with proxy respondents
description
2010 nî lūn-bûn
@nan
2010 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Pattern-mixture models for analyzing normal outcome data with proxy respondents
@ast
Pattern-mixture models for analyzing normal outcome data with proxy respondents
@en
type
label
Pattern-mixture models for analyzing normal outcome data with proxy respondents
@ast
Pattern-mixture models for analyzing normal outcome data with proxy respondents
@en
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Pattern-mixture models for analyzing normal outcome data with proxy respondents
@ast
Pattern-mixture models for analyzing normal outcome data with proxy respondents
@en
P2093
P2860
P356
P1476
Pattern-mixture models for analyzing normal outcome data with proxy respondents
@en
P2093
Jay Magaziner
Michelle Shardell
Patricia Langenberg
Ram R Miller
P2860
P304
P356
10.1002/SIM.3902
P407
P577
2010-06-01T00:00:00Z