-
2
-
-
33644851650
-
Doubly robust estimation in missing data and causal inference models
-
Bang, H. and Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics 61, 962-973.
-
(2005)
Biometrics
, vol.61
, pp. 962-973
-
-
Bang, H.1
Robins, J.M.2
-
4
-
-
0002864224
-
Confounding and collapsibility in causal inference
-
Greenland, S., Robins, J., and Pearl, J. (1999). Confounding and collapsibility in causal inference. Statistical Science 14, 29-46.
-
(1999)
Statistical Science
, vol.14
, pp. 29-46
-
-
Greenland, S.1
Robins, J.2
Pearl, J.3
-
5
-
-
70350537219
-
Stroke patient outcomes in US hospitals before the start of the joint commission primary stroke center certification program
-
Lichtman, J. H., Allen, N. B., Wang, Y., Watanabe, E., Jones, S. B., and Goldstein, L. B. (2009). Stroke patient outcomes in US hospitals before the start of the joint commission primary stroke center certification program. Stroke 40, 3574-3579.
-
(2009)
Stroke
, vol.40
, pp. 3574-3579
-
-
Lichtman, J.H.1
Allen, N.B.2
Wang, Y.3
Watanabe, E.4
Jones, S.B.5
Goldstein, L.B.6
-
6
-
-
83055193550
-
Calibrated bayes, for statistics in general, and missing data in particular
-
Little, R. (2011). Calibrated bayes, for statistics in general, and missing data in particular. Statistical Science 26, 162-174.
-
(2011)
Statistical Science
, vol.26
, pp. 162-174
-
-
Little, R.1
-
7
-
-
84862899262
-
Adjustment for missing confounders using external validation data and propensity scores
-
107, 40-51.
-
McCandless, L., Richardson, S., and Best, N. (2012). Adjustment for missing confounders using external validation data and propensity scores. Journal of the American Statistical Association 107, 40-51.
-
(2012)
Journal of the American Statistical Association
-
-
McCandless, L.1
Richardson, S.2
Best, N.3
-
8
-
-
84866757285
-
Discussion of adjustment uncertainty and propensity scores
-
68, 678-680.
-
McCandless, L. C. (2012). Discussion of adjustment uncertainty and propensity scores. Biometrics 68, 678-680.
-
(2012)
Biometrics
-
-
McCandless, L.C.1
-
9
-
-
77950544211
-
Cutting feedback in bayesian regression adjustment for the propensity score
-
McCandless, L. C., Douglas, I. J., Evans, S. J., and Smeeth, L. (2010). Cutting feedback in bayesian regression adjustment for the propensity score. The International Journal of Biostatistics 6, 1-22.
-
(2010)
The International Journal of Biostatistics
, vol.6
, pp. 1-22
-
-
McCandless, L.C.1
Douglas, I.J.2
Evans, S.J.3
Smeeth, L.4
-
10
-
-
61749103209
-
Bayesian propensity score analysis for observational data
-
McCandless, L. C., Gustafson, P., and Austin, P. C. (2009). Bayesian propensity score analysis for observational data. Statistics in Medicine 28, 94-112.
-
(2009)
Statistics in Medicine
, vol.28
, pp. 94-112
-
-
McCandless, L.C.1
Gustafson, P.2
Austin, P.C.3
-
11
-
-
4444292273
-
Risk adjustment of medicare capitation payments using the CMS-HCC model
-
Pope, G. C., Kautter, J., Ellis, R. P., Ash, A. S., Ayanian, J. Z., Lezzoni, L. I., Ingber, M. J., Levy, J. M., and Robst, J. (2004). Risk adjustment of medicare capitation payments using the CMS-HCC model. Health Care Financing Review 25, 119-141.
-
(2004)
Health Care Financing Review
, vol.25
, pp. 119-141
-
-
Pope, G.C.1
Kautter, J.2
Ellis, R.P.3
Ash, A.S.4
Ayanian, J.Z.5
Lezzoni, L.I.6
Ingber, M.J.7
Levy, J.M.8
Robst, J.9
-
12
-
-
77951622706
-
The central role of the propensity score in observational studies for causal effects
-
Rosenbaum, P. R. and Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55.
-
(1983)
Biometrika
, vol.70
, pp. 41-55
-
-
Rosenbaum, P.R.1
Rubin, D.B.2
-
13
-
-
0542388294
-
The use of propensity scores in applied bayesian inference
-
Valencia, Spain: Elsevier Science Publishers and Valencia University Press
-
Rubin, D. (1985). The use of propensity scores in applied bayesian inference. In Bayesian Statistics, Volume 2, 463-472. Valencia, Spain: Elsevier Science Publishers and Valencia University Press.
-
(1985)
Bayesian Statistics
, vol.2
, pp. 463-472
-
-
Rubin, D.1
-
14
-
-
33846253571
-
The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials
-
Rubin, D. B. (2007). The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Statistics in Medicine 26, 20-36.
-
(2007)
Statistics in Medicine
, vol.26
, pp. 20-36
-
-
Rubin, D.B.1
-
15
-
-
64349088593
-
For objective causal inference, design trumps analysis
-
Rubin, D. B. (2008). For objective causal inference, design trumps analysis. The Annals of Applied Statistics 2, 808-840.
-
(2008)
The Annals of Applied Statistics
, vol.2
, pp. 808-840
-
-
Rubin, D.B.1
-
16
-
-
67651042983
-
High-dimensional propensity score adjustment in studies of treatment effects using health care claims data
-
Schneeweiss, S., Rassen, J. A., Glynn, R. J., Avorn, J., Mogun, H., and Brookhart, M. A. (2009). High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 20, 512-522.
-
(2009)
Epidemiology
, vol.20
, pp. 512-522
-
-
Schneeweiss, S.1
Rassen, J.A.2
Glynn, R.J.3
Avorn, J.4
Mogun, H.5
Brookhart, M.A.6
-
19
-
-
84866746931
-
Bayesian effect estimation accounting for adjustment uncertainty
-
68, 661-671.
-
Wang, C., Parmigiani, G., and Dominici, F. (2012). Bayesian effect estimation accounting for adjustment uncertainty. Biometrics 68, 661-671.
-
(2012)
Biometrics
-
-
Wang, C.1
Parmigiani, G.2
Dominici, F.3
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