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Items: 1 to 20 of 78

1.

Mixed-Poisson Point Process with Partially-Observed Covariates: Ecological Momentary Assessment of Smoking.

Neustifter B, Rathbun SL, Shiffman S.

J Appl Stat. 2012;39(4):883-899. Epub 2012 Mar 12.

2.

Survival Analysis with Time-Varying Covariates Measured at Random Times by Design.

Rathbun SL, Song X, Neustifter B, Shiffman S.

J R Stat Soc Ser C Appl Stat. 2013 May 1;62(3):419-434.

3.

Mixed effects models for recurrent events data with partially observed time-varying covariates: Ecological momentary assessment of smoking.

Rathbun SL, Shiffman S.

Biometrics. 2016 Mar;72(1):46-55. doi: 10.1111/biom.12416. Epub 2015 Sep 27.

4.

ROBUST MIXED EFFECTS MODEL FOR CLUSTERED FAILURE TIME DATA: APPLICATION TO HUNTINGTON'S DISEASE EVENT MEASURES.

Garcia TP, Ma Y, Marder K, Wang Y.

Ann Appl Stat. 2017;11(2):1085-1116. doi: 10.1214/17-AOAS1038. Epub 2017 Jul 20.

5.
6.

Approximate nonparametric corrected-score method for joint modeling of survival and longitudinal data measured with error.

Tapsoba JD, Lee SM, Wang CY.

Biom J. 2011 Jul;53(4):557-77. doi: 10.1002/bimj.201000180. Erratum in: Biom J. 2015 Jul;57(4):720. de Dieu Tapsoba, Jean [corrected to Tapsoba, Jean D].

7.

A 3-level Bayesian mixed effects location scale model with an application to ecological momentary assessment data.

Lin X, Mermelstein RJ, Hedeker D.

Stat Med. 2018 Jun 15;37(13):2108-2119. doi: 10.1002/sim.7627. Epub 2018 Feb 26.

8.

Modeling mood variation associated with smoking: an application of a heterogeneous mixed-effects model for analysis of ecological momentary assessment (EMA) data.

Hedeker D, Mermelstein RJ, Berbaum ML, Campbell RT.

Addiction. 2009 Feb;104(2):297-307. doi: 10.1111/j.1360-0443.2008.02435.x.

9.

A measurement error model with a Poisson distributed surrogate.

Li L, Palta M, Shao J.

Stat Med. 2004 Aug 30;23(16):2527-36.

PMID:
15287082
10.

A mixed ordinal location scale model for analysis of Ecological Momentary Assessment (EMA) data.

Hedeker D, Demirtas H, Mermelstein RJ.

Stat Interface. 2009;2(4):391-401.

11.

Semiparametric estimation of the accelerated mean model with panel count data under informative examination times.

Chiou SH, Xu G, Yan J, Huang CY.

Biometrics. 2018 Sep;74(3):944-953. doi: 10.1111/biom.12840. Epub 2017 Dec 29.

12.

Survival analysis of clinical mastitis data using a nested frailty Cox model fit as a mixed-effects Poisson model.

Elghafghuf A, Dufour S, Reyher K, Dohoo I, Stryhn H.

Prev Vet Med. 2014 Dec 1;117(3-4):456-68. doi: 10.1016/j.prevetmed.2014.09.013. Epub 2014 Oct 5.

PMID:
25449735
13.

An application of a mixed-effects location scale model for analysis of Ecological Momentary Assessment (EMA) data.

Hedeker D, Mermelstein RJ, Demirtas H.

Biometrics. 2008 Jun;64(2):627-34. Epub 2007 Oct 26.

14.

Estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers.

Li S, Ning Y.

Biometrics. 2015 Sep;71(3):666-76. doi: 10.1111/biom.12312. Epub 2015 Apr 17.

15.

Modeling between-subject and within-subject variances in ecological momentary assessment data using mixed-effects location scale models.

Hedeker D, Mermelstein RJ, Demirtas H.

Stat Med. 2012 Nov 30;31(27):3328-36. doi: 10.1002/sim.5338. Epub 2012 Mar 15.

16.

Analysis of multi-type recurrent events in longitudinal studies; application to a skin cancer prevention trial.

Abu-Libdeh H, Turnbull BW, Clark LC.

Biometrics. 1990 Dec;46(4):1017-34.

PMID:
2085623
17.

Semiparametric estimation of the covariate-specific ROC curve in presence of ignorable verification bias.

Liu D, Zhou XH.

Biometrics. 2011 Sep;67(3):906-16. doi: 10.1111/j.1541-0420.2011.01562.x. Epub 2011 Mar 1.

18.

Collaborative double robust targeted maximum likelihood estimation.

van der Laan MJ, Gruber S.

Int J Biostat. 2010 May 17;6(1):Article 17. doi: 10.2202/1557-4679.1181.

19.

On the proportional hazards model for occupational and environmental case-control analyses.

Gauvin H, Lacourt A, Leffondré K.

BMC Med Res Methodol. 2013 Feb 15;13:18. doi: 10.1186/1471-2288-13-18.

20.

Poisson regression models outperform the geometrical model in estimating the peak-to-trough ratio of seasonal variation: a simulation study.

Christensen AL, Lundbye-Christensen S, Dethlefsen C.

Comput Methods Programs Biomed. 2011 Dec;104(3):333-40. doi: 10.1016/j.cmpb.2011.07.016. Epub 2011 Oct 11.

PMID:
21996029

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