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Items: 1 to 20 of 93

1.

Design considerations for case series models with exposure onset measurement error.

Mohammed SM, Dalrymple LS, Sentürk D, Nguyen DV.

Stat Med. 2013 Feb 28;32(5):772-86. doi: 10.1002/sim.5552. Epub 2012 Aug 22.

2.

Measurement Error Case Series Models with Application to Infection-Cardiovascular Risk in OlderPatients on Dialysis.

Mohammed SM, Sentürk D, Dalrymple LS, Nguyen DV.

J Am Stat Assoc. 2012 Dec 1;107(500):1310-1323.

3.

Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular mortality in the Netherlands: the NLCS-AIR study.

Brunekreef B, Beelen R, Hoek G, Schouten L, Bausch-Goldbohm S, Fischer P, Armstrong B, Hughes E, Jerrett M, van den Brandt P.

Res Rep Health Eff Inst. 2009 Mar;(139):5-71; discussion 73-89.

PMID:
19554969
4.

Naive hypothesis testing for case series analysis with time-varying exposure onset measurement error: inference for infection-cardiovascular risk in patients on dialysis.

Mohammed SM, Dalrymple LS, Şentürk D, Nguyen DV.

Biometrics. 2013 Jun;69(2):520-9. doi: 10.1111/biom.12033. Epub 2013 Jun 3.

5.

Sample size considerations for the external validation of a multivariable prognostic model: a resampling study.

Collins GS, Ogundimu EO, Altman DG.

Stat Med. 2016 Jan 30;35(2):214-26. doi: 10.1002/sim.6787. Epub 2015 Nov 9.

6.

Impact of the 1990 Hong Kong legislation for restriction on sulfur content in fuel.

Wong CM, Rabl A, Thach TQ, Chau YK, Chan KP, Cowling BJ, Lai HK, Lam TH, McGhee SM, Anderson HR, Hedley AJ.

Res Rep Health Eff Inst. 2012 Aug;(170):5-91.

PMID:
23316618
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10.

Analysis of Clinical Cohort Data Using Nested Case-control and Case-cohort Sampling Designs. A Powerful and Economical Tool.

Ohneberg K, Wolkewitz M, Beyersmann J, Palomar-Martinez M, Olaechea-Astigarraga P, Alvarez-Lerma F, Schumacher M.

Methods Inf Med. 2015;54(6):505-14. doi: 10.3414/ME14-01-0113. Epub 2015 Jun 25.

PMID:
26108707
11.

Robust best linear estimation for regression analysis using surrogate and instrumental variables.

Wang CY.

Biostatistics. 2012 Apr;13(2):326-40. doi: 10.1093/biostatistics/kxr051. Epub 2012 Jan 27.

12.

Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application.

Chu H, Cole SR, Wei Y, Ibrahim JG.

Biostatistics. 2009 Oct;10(4):591-602. doi: 10.1093/biostatistics/kxp015. Epub 2009 Jun 9.

13.

Sample size planning for survival prediction with focus on high-dimensional data.

Götte H, Zwiener I.

Stat Med. 2013 Feb 28;32(5):787-807. doi: 10.1002/sim.5550. Epub 2012 Aug 1.

PMID:
22859340
15.

Instrumental variables vs. grouping approach for reducing bias due to measurement error.

Batistatou E, McNamee R.

Int J Biostat. 2008;4(1):Article 8.

PMID:
22462115
16.

A two-stage strategy to accommodate general patterns of confounding in the design of observational studies.

Haneuse S, Schildcrout J, Gillen D.

Biostatistics. 2012 Apr;13(2):274-88. doi: 10.1093/biostatistics/kxr044. Epub 2011 Nov 30.

17.

Power estimation using simulations for air pollution time-series studies.

Winquist A, Klein M, Tolbert P, Sarnat SE.

Environ Health. 2012 Sep 20;11:68. doi: 10.1186/1476-069X-11-68.

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A heteroscedastic measurement error model for method comparison data with replicate measurements.

Nawarathna LS, Choudhary PK.

Stat Med. 2015 Mar 30;34(7):1242-58. doi: 10.1002/sim.6424. Epub 2015 Jan 23.

PMID:
25614299
20.

Regression-assisted deconvolution.

McIntyre J, Stefanski LA.

Stat Med. 2011 Jun 30;30(14):1722-34. doi: 10.1002/sim.4186. Epub 2011 Feb 1.

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