| Year |
Citation |
Score |
| 2020 |
Scotina AD, Zullo AR, Smith RJ, Gutman R. Approximate Bayesian Bootstrap procedures to estimate multilevel treatment effects in observational studies with application to type 2 diabetes treatment regimens. Statistical Methods in Medical Research. 962280220928109. PMID 32588747 DOI: 10.1177/0962280220928109 |
0.352 |
|
| 2020 |
Roydhouse J, Gutman R, Keating N, Wilson I. Propensity scores for proxy reports of care experience and quality: are they useful? Health Services and Outcomes Research Methodology. 20: 40-59. DOI: 10.1007/S10742-019-00205-4 |
0.334 |
|
| 2019 |
Scotina AD, Beaudoin FL, Gutman R. Matching estimators for causal effects of multiple treatments. Statistical Methods in Medical Research. 962280219850858. PMID 31138025 DOI: 10.1177/0962280219850858 |
0.351 |
|
| 2019 |
Scotina AD, Gutman R. Matching algorithms for causal inference with multiple treatments. Statistics in Medicine. PMID 31066079 DOI: 10.1002/Sim.8147 |
0.326 |
|
| 2019 |
Gu C, Gutman R. Development of a common patient assessment scale across the continuum of care: A nested multiple imputation approach The Annals of Applied Statistics. 13: 466-491. DOI: 10.1214/18-Aoas1202 |
0.33 |
|
| 2019 |
Silva GC, Trivedi AN, Gutman R. Developing and evaluating methods to impute race/ethnicity in an incomplete dataset Health Services and Outcomes Research Methodology. 19: 175-195. DOI: 10.1007/S10742-019-00200-9 |
0.332 |
|
| 2017 |
Lopez MJ, Gutman R. Estimation of Causal Effects with Multiple Treatments: A Review and New Ideas Statistical Science. 32: 432-454. DOI: 10.1214/17-Sts612 |
0.344 |
|
| 2016 |
Gu C, Gutman R. Combining item response theory with multiple imputation to equate health assessment questionnaires. Biometrics. PMID 27936287 DOI: 10.1111/Biom.12638 |
0.328 |
|
| 2015 |
Gutman R, Sammartino CJ, Green TC, Montague BT. Error adjustments for file linking methods using encrypted unique client identifier (eUCI) with application to recently released prisoners who are HIV. Statistics in Medicine. PMID 26202853 DOI: 10.1002/Sim.6586 |
0.312 |
|
| 2015 |
Gutman R, Rubin DB. Estimation of causal effects of binary treatments in unconfounded studies. Statistics in Medicine. PMID 26013308 DOI: 10.1002/Sim.6532 |
0.521 |
|
| 2015 |
Gutman R, Rubin D. Estimation of causal effects of binary treatments in unconfounded studies with one continuous covariate. Statistical Methods in Medical Research. PMID 25715391 DOI: 10.1177/0962280215570722 |
0.517 |
|
| 2014 |
Lopez MJ, Gutman R. Estimating the average treatment effects of nutritional label use using subclassification with regression adjustment. Statistical Methods in Medical Research. PMID 25432690 DOI: 10.1177/0962280214560046 |
0.303 |
|
| 2013 |
Dore DD, Swaminathan S, Gutman R, Trivedi AN, Mor V. Different analyses estimate different parameters of the effect of erythropoietin stimulating agents on survival in end stage renal disease: a comparison of payment policy analysis, instrumental variables, and multiple imputation of potential outcomes. Journal of Clinical Epidemiology. 66: S42-50. PMID 23849152 DOI: 10.1016/J.Jclinepi.2013.02.014 |
0.328 |
|
| 2013 |
Gutman R, Rubin DB. Robust estimation of causal effects of binary treatments in unconfounded studies with dichotomous outcomes. Statistics in Medicine. 32: 1795-814. PMID 23019093 DOI: 10.1002/Sim.5627 |
0.518 |
|
| 2012 |
Gutman R, Rubin DB. Analyses that inform policy decisions. Biometrics. 68: 671-5; discussion 68. PMID 22455379 DOI: 10.1111/J.1541-0420.2011.01732.X |
0.418 |
|
| 2009 |
Cangul MZ, Chretien YR, Gutman R, Rubin DB. Testing treatment effects in unconfounded studies under model misspecification: logistic regression, discretization, and their combination. Statistics in Medicine. 28: 2531-51. PMID 19572258 DOI: 10.1002/Sim.3633 |
0.607 |
|
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