Julia Y. Lin
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Julia Y. Lin has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Thomas R. Ten Have
Department of Biostatistics and Epidemiology
2 shared publications Hillary R. Bogner
Department of Family Practice and Community Medicine, School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, U.S.A.
1 shared publicationMichael R. Elliott
Department of Biostatistics, School of Public Health, and Survey Methodology Program, Institute for Social Research, University of Michigan, Ann Arbor, MI 48109, U.S.A.
1 shared publication- Michael R. Elliott
University of Michigan School of Public Health, Ann Arbor, USA
1 shared publication
Latest Publications
- 28 May 2009
- Published by Oxford University Press (OUP) in Biometrics
- Vol. 65 (2) , 505-513
Nested Markov Compliance Class Model in the Presence of Time‐Varying Noncompliance
Summary We consider a Markov structure for partially unobserved time‐varying compliance classes in the Imbens–Rubin (1997, The Annals of Statistics25, 305–327) compliance model framework. The context is a longitudinal randomized intervention study where subjects are randomized once at baseline, outcomes and patient adherence are measured at multiple follow‐ups, and patient adherence to their randomized treatment could vary over time. We propose a nested latent compliance class model where we use time‐invariant subject‐specific compliance principal strata to summarize longitudinal trends of subject‐specific time‐varying compliance patterns. The principal strata are formed using Markov models that relate current compliance behavior to compliance history. Treatment effects are estimated as intent‐to‐treat effects within the compliance principal strata.
- 28 May 2009
- Published by Oxford University Press (OUP) in Biometrics
- Vol. 65 (2) , 505-513
Nested Markov Compliance Class Model in the Presence of Time‐Varying Noncompliance
Summary We consider a Markov structure for partially unobserved time‐varying compliance classes in the Imbens–Rubin (1997, The Annals of Statistics25, 305–327) compliance model framework. The context is a longitudinal randomized intervention study where subjects are randomized once at baseline, outcomes and patient adherence are measured at multiple follow‐ups, and patient adherence to their randomized treatment could vary over time. We propose a nested latent compliance class model where we use time‐invariant subject‐specific compliance principal strata to summarize longitudinal trends of subject‐specific time‐varying compliance patterns. The principal strata are formed using Markov models that relate current compliance behavior to compliance history. Treatment effects are estimated as intent‐to‐treat effects within the compliance principal strata.
- 3 May 2007
- Published by Wiley in Statistics in Medicine
- Vol. 26 (28) , 5100-5115
Baseline patient characteristics and mortality associated with longitudinal intervention compliance
- 3 May 2007
- Published by Wiley in Statistics in Medicine
- Vol. 26 (28) , 5100-5115
Baseline patient characteristics and mortality associated with longitudinal intervention compliance