-
2
-
-
77951622706
-
The central role of the propensity score in observational studies for causal effects
-
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70:41-55.
-
(1983)
Biometrika
, vol.70
, pp. 41-55
-
-
Rosenbaum, P.R.1
Rubin, D.B.2
-
3
-
-
10844259913
-
Principles for modeling propensity scores in medical research: a systematic literature review
-
Weitzen S, Lapane KL, Toledano AY, Hume AL, Mor V. Principles for modeling propensity scores in medical research: a systematic literature review. Pharmacoepidemiology and Drug Safety 2004; 13(12):841-853.
-
(2004)
Pharmacoepidemiology and Drug Safety
, vol.13
, Issue.12
, pp. 841-853
-
-
Weitzen, S.1
Lapane, K.L.2
Toledano, A.Y.3
Hume, A.L.4
Mor, V.5
-
4
-
-
44649173785
-
A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003
-
Austin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Statistics in Medicine 2008; 27(12):2037-2049.
-
(2008)
Statistics in Medicine
, vol.27
, Issue.12
, pp. 2037-2049
-
-
Austin, P.C.1
-
5
-
-
72749123968
-
A substantial and confusing variation exists in handling of baseline covariates in randomized controlled trials: a review of trials published in leading medical journals
-
Austin PC, Manca A, Zwarenstein M, Juurlink DN, Stanbrook MB. A substantial and confusing variation exists in handling of baseline covariates in randomized controlled trials: a review of trials published in leading medical journals. Journal of Clinical Epidemiology 2010; 63(2):142-153.
-
(2010)
Journal of Clinical Epidemiology
, vol.63
, Issue.2
, pp. 142-153
-
-
Austin, P.C.1
Manca, A.2
Zwarenstein, M.3
Juurlink, D.N.4
Stanbrook, M.B.5
-
6
-
-
33846813595
-
Conditioning on the propensity score can result in biased estimation of common measures of treatment effect: a Monte Carlo study
-
Austin PC, Grootendorst P, Normand SL, Anderson GM. Conditioning on the propensity score can result in biased estimation of common measures of treatment effect: a Monte Carlo study. Statistics in Medicine 2007; 26(4):754-768.
-
(2007)
Statistics in Medicine
, vol.26
, Issue.4
, pp. 754-768
-
-
Austin, P.C.1
Grootendorst, P.2
Normand, S.L.3
Anderson, G.M.4
-
7
-
-
34249863765
-
The performance of different propensity score methods for estimating marginal odds ratios
-
Austin PC. The performance of different propensity score methods for estimating marginal odds ratios. Statistics in Medicine 2007; 26(16):3078-3094.
-
(2007)
Statistics in Medicine
, vol.26
, Issue.16
, pp. 3078-3094
-
-
Austin, P.C.1
-
8
-
-
43049162150
-
The performance of different propensity-score methods for estimating relative risks
-
Austin PC. The performance of different propensity-score methods for estimating relative risks. Journal of Clinical Epidemiology 2008; 61(6):537-545.
-
(2008)
Journal of Clinical Epidemiology
, vol.61
, Issue.6
, pp. 537-545
-
-
Austin, P.C.1
-
9
-
-
77956314484
-
The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies
-
Austin PC. The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies. Statistics in Medicine 2010; 29(20):2137-2148.
-
(2010)
Statistics in Medicine
, vol.29
, Issue.20
, pp. 2137-2148
-
-
Austin, P.C.1
-
10
-
-
0023203943
-
Interpretation and choice of effect measures in epidemiologic analyses
-
Greenland S. Interpretation and choice of effect measures in epidemiologic analyses. American Journal of Epidemiology 1987; 125(5):761-768.
-
(1987)
American Journal of Epidemiology
, vol.125
, Issue.5
, pp. 761-768
-
-
Greenland, S.1
-
11
-
-
77956891487
-
Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates
-
Gail MH, Wieand S, Piantadosi S. Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates. Biometrika 1984; 7:431-444.
-
(1984)
Biometrika
, vol.7
, pp. 431-444
-
-
Gail, M.H.1
Wieand, S.2
Piantadosi, S.3
-
12
-
-
33645217214
-
Propensity score
-
In, Armitage P, Colton T (eds). John Wiley & Sons: Boston
-
Rosenbaum PR. Propensity score. In Encyclopedia of Biostatistics, Armitage P, Colton T (eds). John Wiley & Sons: Boston, 2005; 4267-4272.
-
(2005)
Encyclopedia of Biostatistics
, pp. 4267-4272
-
-
Rosenbaum, P.R.1
-
13
-
-
84945581878
-
Constructing a control group using multivariate matched sampling methods that incorporate the propensity score
-
Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician 1985; 39:33-38.
-
(1985)
The American Statistician
, vol.39
, pp. 33-38
-
-
Rosenbaum, P.R.1
Rubin, D.B.2
-
14
-
-
77958600686
-
Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies
-
Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharmaceutical Statistics 2010; 10:150-161.
-
(2010)
Pharmaceutical Statistics
, vol.10
, pp. 150-161
-
-
Austin, P.C.1
-
17
-
-
84949193513
-
Reducing bias in observational studies using subclassification on the propensity score
-
Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association 1984; 79:516-524.
-
(1984)
Journal of the American Statistical Association
, vol.79
, pp. 516-524
-
-
Rosenbaum, P.R.1
Rubin, D.B.2
-
18
-
-
0014297593
-
The effectiveness of adjustment by subclassification in removing bias in observational studies
-
Cochran WG. The effectiveness of adjustment by subclassification in removing bias in observational studies. Biometrics 1968; 24(2):295-313.
-
(1968)
Biometrics
, vol.24
, Issue.2
, pp. 295-313
-
-
Cochran, W.G.1
-
19
-
-
4444230264
-
Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study
-
Lunceford JK, Davidian M. Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study. Statistics in Medicine 2004; 23(19):2937-2960.
-
(2004)
Statistics in Medicine
, vol.23
, Issue.19
, pp. 2937-2960
-
-
Lunceford, J.K.1
Davidian, M.2
-
20
-
-
54049137609
-
A diagnostic routine for the detection of consequential heterogeneity of causal effects
-
Morgan SL, Todd JL. A diagnostic routine for the detection of consequential heterogeneity of causal effects. Sociological Methodology 2008; 38:231-281.
-
(2008)
Sociological Methodology
, vol.38
, pp. 231-281
-
-
Morgan, S.L.1
Todd, J.L.2
-
21
-
-
8744315994
-
Model selection, confounder control, and marginal structural models: Review and new applications
-
Joffe MM, Ten Have TR, Feldman HI, Kimmel SE. Model selection, confounder control, and marginal structural models: Review and new applications. The American Statistician 2004; 58:272-279.
-
(2004)
The American Statistician
, vol.58
, pp. 272-279
-
-
Joffe, M.M.1
Ten Have, T.R.2
Feldman, H.I.3
Kimmel, S.E.4
-
22
-
-
19944372078
-
Generating survival times to simulate Cox proportional hazards models
-
Bender R, Augustin T, Blettner M. Generating survival times to simulate Cox proportional hazards models. Statistics in Medicine 2005; 24(11):1713-1723.
-
(2005)
Statistics in Medicine
, vol.24
, Issue.11
, pp. 1713-1723
-
-
Bender, R.1
Augustin, T.2
Blettner, M.3
-
23
-
-
77349087330
-
A data-generation process for data with specified risk differences or numbers needed to treat
-
DOI: 10.1080/03610910903528301.
-
Austin PC. A data-generation process for data with specified risk differences or numbers needed to treat. Communications in Statistics - Simulation and Computation 2010; 39:563-577. DOI: 10.1080/03610910903528301.
-
(2010)
Communications in Statistics - Simulation and Computation
, vol.39
, pp. 563-577
-
-
Austin, P.C.1
-
24
-
-
47749131861
-
The performance of two data-generation processes for data with specified marginal treatment odds ratios
-
Austin PC, Stafford J. The performance of two data-generation processes for data with specified marginal treatment odds ratios. Communications in Statistics - Simulation and Computation 2008; 37:1039-1051.
-
(2008)
Communications in Statistics - Simulation and Computation
, vol.37
, pp. 1039-1051
-
-
Austin, P.C.1
Stafford, J.2
-
25
-
-
33846842327
-
A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study
-
Austin PC, Grootendorst P, Anderson GM. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study. Statistics in Medicine 2007; 26(4):734-753.
-
(2007)
Statistics in Medicine
, vol.26
, Issue.4
, pp. 734-753
-
-
Austin, P.C.1
Grootendorst, P.2
Anderson, G.M.3
-
26
-
-
0002512643
-
A comparison of cluster-specific and population-averaged approaches for analyzing correlated binary data
-
Neuhaus JM, Kalbfleish JD, Hauck WW. A comparison of cluster-specific and population-averaged approaches for analyzing correlated binary data. International Statistical Review 1991; 59(1):25-35.
-
(1991)
International Statistical Review
, vol.59
, Issue.1
, pp. 25-35
-
-
Neuhaus, J.M.1
Kalbfleish, J.D.2
Hauck, W.W.3
-
27
-
-
0037108235
-
Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems
-
Pocock SJ, Assmann SE, Enos LE, Kasten LE. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Statistics in Medicine 2002; 21(19):2917-2930.
-
(2002)
Statistics in Medicine
, vol.21
, Issue.19
, pp. 2917-2930
-
-
Pocock, S.J.1
Assmann, S.E.2
Enos, L.E.3
Kasten, L.E.4
-
28
-
-
67249097811
-
Type I error rates, coverage of confidence intervals, and variance estimation in propensity-score matched analyses
-
Article 13. DOI: 10.2202/1557-4679.1146.
-
Austin PC. Type I error rates, coverage of confidence intervals, and variance estimation in propensity-score matched analyses. International Journal of Biostatistics 2009; 5: Article 13. DOI: 10.2202/1557-4679.1146.
-
(2009)
International Journal of Biostatistics
, vol.5
-
-
Austin, P.C.1
-
30
-
-
27144479267
-
Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data
-
Xie J, Liu C. Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data. Statistics in Medicine 2005; 24(20):3089-3110.
-
(2005)
Statistics in Medicine
, vol.24
, Issue.20
, pp. 3089-3110
-
-
Xie, J.1
Liu, C.2
-
31
-
-
74749097452
-
Improving propensity score weighting using machine learning
-
Lee BK, Lessler J, Stuart EA. Improving propensity score weighting using machine learning. Statistics in Medicine 2010; 29(3):337-346.
-
(2010)
Statistics in Medicine
, vol.29
, Issue.3
, pp. 337-346
-
-
Lee, B.K.1
Lessler, J.2
Stuart, E.A.3
-
32
-
-
46349084991
-
Evaluating uses of data mining techniques in propensity score estimation: a simulation study
-
Setoguchi S, Schneeweiss S, Brookhart MA, Glynn RJ, Cook EF. Evaluating uses of data mining techniques in propensity score estimation: a simulation study. Pharmacoepidemiolgy and Drug Safety 2008; 17(6):546-555.
-
(2008)
Pharmacoepidemiolgy and Drug Safety
, vol.17
, Issue.6
, pp. 546-555
-
-
Setoguchi, S.1
Schneeweiss, S.2
Brookhart, M.A.3
Glynn, R.J.4
Cook, E.F.5
-
33
-
-
77958523826
-
Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score
-
Austin PC. Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score. American Journal of Epidemiology 2010; 172(9):1092-1097.
-
(2010)
American Journal of Epidemiology
, vol.172
, Issue.9
, pp. 1092-1097
-
-
Austin, P.C.1
-
34
-
-
60849116685
-
Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and Monte Carlo simulations
-
Austin PC. Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and Monte Carlo simulations. Biometrical Journal 2009; 51(1):171-184.
-
(2009)
Biometrical Journal
, vol.51
, Issue.1
, pp. 171-184
-
-
Austin, P.C.1
-
36
-
-
79955639125
-
Comparing paired vs non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples
-
Austin PC. Comparing paired vs non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples. Statistics in Medicine 2011; 30(11):1292-1301.
-
(2011)
Statistics in Medicine
, vol.30
, Issue.11
, pp. 1292-1301
-
-
Austin, P.C.1
-
37
-
-
84861097401
-
Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study
-
DOI: 10.1002/pst.537.
-
Gayat E, Resche-Rigon M, Mary JY, Porcher R. Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study. Pharmaceutical Statistics 2012; 11(3):222-229, DOI: 10.1002/pst.537.
-
(2012)
Pharmaceutical Statistics
, vol.11
, Issue.3
, pp. 222-229
-
-
Gayat, E.1
Resche-Rigon, M.2
Mary, J.Y.3
Porcher, R.4
|