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Items: 1 to 20 of 133

2.

Re: The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials.

Shrier I.

Stat Med. 2008 Jun 30;27(14):2740-1; author reply 2741-2. No abstract available.

PMID:
18069729
3.

Developments in cluster randomized trials and Statistics in Medicine.

Campbell MJ, Donner A, Klar N.

Stat Med. 2007 Jan 15;26(1):2-19.

PMID:
17136746
4.

[Propensity score methods for creating covariate balance in observational studies].

Pattanayak CW, Rubin DB, Zell ER.

Rev Esp Cardiol. 2011 Oct;64(10):897-903. doi: 10.1016/j.recesp.2011.06.008. Epub 2011 Aug 27. Review. Spanish.

5.

Addressing the issue of channeling bias in observational studies with propensity scores analysis.

Lobo FS, Wagner S, Gross CR, Schommer JC.

Res Social Adm Pharm. 2006 Mar;2(1):143-51.

PMID:
17138506
6.

Propensity score estimation with missing values using a multiple imputation missingness pattern (MIMP) approach.

Qu Y, Lipkovich I.

Stat Med. 2009 Apr 30;28(9):1402-14. doi: 10.1002/sim.3549.

PMID:
19222021
7.
8.

Principal stratification with predictors of compliance for randomized trials with 2 active treatments.

Roy J, Hogan JW, Marcus BH.

Biostatistics. 2008 Apr;9(2):277-89. Epub 2007 Aug 6.

PMID:
17681993
9.

[Controlled randomized clinical trials].

Jaillon P.

Bull Acad Natl Med. 2007 Apr-May;191(4-5):739-56; discussion 756-8. French.

PMID:
18225427
10.

Remarks on the method of propensity score.

Pearl J.

Stat Med. 2009 Apr 30;28(9):1415-6; author reply 1420-3. doi: 10.1002/sim.3521. No abstract available.

PMID:
19340847
11.

Evidence from nonrandomized studies: a case study on the estimation of causal effects.

Schmoor C, Caputo A, Schumacher M.

Am J Epidemiol. 2008 May 1;167(9):1120-9. doi: 10.1093/aje/kwn010. Epub 2008 Mar 11.

PMID:
18334500
12.

Nonparametric adjustment techniques for binary covariates.

Berger VW.

Biom J. 2005 Apr;47(2):199-205.

PMID:
16389917
13.

A definition of causal effect for epidemiological research.

Hernán MA.

J Epidemiol Community Health. 2004 Apr;58(4):265-71.

14.

ITT analysis of randomized encouragement design studies with missing data.

Zhou XH, Li SM.

Stat Med. 2006 Aug 30;25(16):2737-61.

PMID:
16287216
15.

Bayesian statistical inference enhances the interpretation of contemporary randomized controlled trials.

Wijeysundera DN, Austin PC, Hux JE, Beattie WS, Laupacis A.

J Clin Epidemiol. 2009 Jan;62(1):13-21.e5. doi: 10.1016/j.jclinepi.2008.07.006. Epub 2008 Oct 23.

PMID:
18947971
16.

Assessing balance in measured baseline covariates when using many-to-one matching on the propensity-score.

Austin PC.

Pharmacoepidemiol Drug Saf. 2008 Dec;17(12):1218-25. doi: 10.1002/pds.1674.

PMID:
18972455
17.

Estimating causal effects from large data sets using propensity scores.

Rubin DB.

Ann Intern Med. 1997 Oct 15;127(8 Pt 2):757-63. Review.

PMID:
9382394
18.
19.

Discussion of "Identifiability and estimation of causal effects in randomized trials with noncompliance and completely nonignorable missing data".

Small DS, Cheng J.

Biometrics. 2009 Sep;65(3):682-6; discussion 689-91. doi: 10.1111/j.1541-0420.2008.01121.x. Epub 2008 Aug 28. No abstract available.

PMID:
18759846
20.

Propensity scores and M-structures.

Sjölander A.

Stat Med. 2009 Apr 30;28(9):1416-20; author reply 1420-3. doi: 10.1002/sim.3532.

PMID:
19340845

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