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Theory and Methods - Rejoinder - Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
Scharfstein, Daniel O.; Rotnitzky, Andrea; Robins, James M. - In: Journal of the American Statistical Association : JASA 94 (1999) 448, pp. 1135-1146
Persistent link: https://www.econbiz.de/10006625909
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Theory and Methods - Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
Scharfstein, Daniel O.; Rotnitzky, Andrea; Robins, James M. - In: Journal of the American Statistical Association : JASA 94 (1999) 448, pp. 1096-1120
Persistent link: https://www.econbiz.de/10006625916
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Theory and Methods - Semiparametric Regression for Repeated Outcomes With Nonignorable Nonresponse
Rotnitzky, Andrea; Robins, James M.; Scharfstein, Daniel O. - In: Journal of the American Statistical Association : JASA 93 (1998) 444, pp. 1321-1339
Persistent link: https://www.econbiz.de/10006627930
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Theory and Methods - Semiparametric Regression for Repeated Outcomes With Nonignorable Nonresponse
Rotnitzky, Andrea; Robins, James M.; Scharfstein, Daniel O. - In: Journal of the American Statistical Association : JASA 19980, pp. 1321-1339
Persistent link: https://www.econbiz.de/10006640033
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Brand versus generic : addressing non‐adherence, secular trends and non‐overlap
Hunt, Lamar; Murimi, Irene B.; Segal, Jodi B.; Seamans, … - In: Journal of the Royal Statistical Society: Series A … 183 (2020) 4, pp. 1461-1478
Persistent link: https://www.econbiz.de/10012284173
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Generalized Additive Selection Models for the Analysis of Studies with Potentially Nonignorable Missing Outcome Data
Scharfstein, Daniel O.; Irizarry, Rafael A. - In: Biometrics 59 (2003) 3, pp. 601-613
Persistent link: https://www.econbiz.de/10010947064
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On the Construction of Bounds in Prospective Studies with Missing Ordinal Outcomes: Application to the Good Behavior Game Trial
Scharfstein, Daniel O.; Manski, Charles F.; Anthony, … - In: Biometrics 60 (2004) 1, pp. 154-164
Persistent link: https://www.econbiz.de/10010947253
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On Estimation of the Survivor Average Causal Effect in Observational Studies When Important Confounders Are Missing Due to Death
Egleston, Brian L.; Scharfstein, Daniel O.; MacKenzie, Ellen - In: Biometrics 65 (2009) 2, pp. 497-504
Persistent link: https://www.econbiz.de/10010947359
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Design of Developmental Toxicity Studies for Assessing Joint Effects of Dose and Duration
Scharfstein, Daniel O.; Williams, Paige L. - In: Risk analysis : an international journal 14 (1994) 6, pp. 1057-1072
Persistent link: https://www.econbiz.de/10006866979
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Analysis of longitudinal data with irregular, outcome-dependent follow-up
Lin, Haiqun; Scharfstein, Daniel O.; Rosenheck, Robert A. - In: Journal of the Royal Statistical Society Series B 66 (2004) 3, pp. 791-813
A frequent problem in longitudinal studies is that subjects may miss scheduled visits or be assessed at self-selected points in time. As a result, observed outcome data may be highly unbalanced and the availability of the data may be directly related to the outcome measure and/or some auxiliary...
Persistent link: https://www.econbiz.de/10005140234