Papers

  • Baiocchi, M., Small, D., Yang, L., Polsky, D. and Groeneveld, P. Near/far matching-- a study design approach to instrumental variables. Health Services and Outcomes Research Methodology, in press.

  • Lorch, S., Baiocchi, M., Ahlberg, C. and Small, D. The differential impact of delivery hospital on the outcomes of premature infants. Pediatrics, in press.

  • Cai, B., Hennessy, S., Flory, J., Sha, D, Ten Have, T. and Small, D. Simulation study of instrumental variable approaches with an application to a study of the antidiabetic effect of bezafibrate. Pharmacoepidemiology and Drug Safety, in press. Appendix. SAS macro ( Documentation).

  • Yang, D. and Small, D. An R package and a study of methods for computing empirical likelihood. Journal of Statistical Computation and Simulation, in press. R package.

  • Luo, X., Small, D., Li, C. and Rosenbaum, P. Inference with interference in an fMRI experiment of motor inhibition. Journal of the American Statistical Association, in press.

  • Tustin, A., Small, D., Delgado, S., Castillo Neyra, R., Verastegui, M., Ancca Juarez, J., Quispe Machaca, M., Gilman, R., Bern, C. and Levy, M. Use of individual level covariates to improve latent class analysis of Trypanosoma cruzi diagnostic tests. Epidemiologic Methods, in press.

  • Yang, D., Small, D., Silber, J. and Rosenbaum, P. Optimal matching with minimal deviation from fine balance in a study of obesity and surgical outcomes. Biometrics, in press. Supplementary Materials.

  • Zhang, K., Traskin, M. and Small, D. (2012) A powerful and robust test statistic for randomization inference in group-randomized trials with matched pairs of groups. Biometrics, 68, 75-84.

  • Okui, R., Small, D., Tan, Z. and Robins, J. (2012). Doubly robust instrumental variables regression. Statistica Sinca, 22, 173-205.

  • Levy, M., Small, D., Vilhena, D., Bowman, N., Kawai, V., Cornejo del-Carpio, J., Cordova-Benzaquen, E., Gilman, R., Bern, C. and Plotkin, J. (2011). Retracing micro-epidemics of Chagas disease using epicenter regression. PLoS Computational Biology, 7, 1002146.

  • Traskin, M. and Small, D. (2011). Defining the study population for an observational study to ensure sufficient overlap: a tree approach. Statistics in Biosciences, 3, 94-118. Supplementary Materials.

  • Zhang, K., Small, D., Lorch, S., Srinivas, S. and Rosenbaum, P. (2011). Using split samples and evidence factors in an observational study of neonatal outcomes, Journal of the American Statistical Association, 106, 511-524.

  • Cai, B., Small, D. and Ten Have, T. (2011). Two-stage instrumental variable methods for estimating the causal odds ratio: analysis of bias. Statistics in Medicine, 30, 1809-1824.

  • Small, D., Volpp, K. and Rosenbaum, P. (2011). Structured testing of 2x2 factorial effects: an analytic plan requiring fewer observations. The American Statistician, 65, 11-15.

  • Nie, H., Cheng, J. and Small, D. (2011). Inference for the effect of treatment on survival probability in randomized trials with noncompliance and administrative censoring. Biometrics, 67, 1397-1405. Web Appendix

  • Han, X., Small, D., Foster, D. and Patel, V. (2011). The effect of winning an Oscar award on survival: correcting for healthy performer survivor bias with a rank preserving structural accelerated failure time model. Annals of Applied Statistics, 5, 746-772.

  • Zhang, M., Joffe, M. and Small, D. (2011). Causal inference for continuous time processes when covariates are observed only at discrete times. Annals of Statistics, 39, 131-173.

  • Heller, R., Rosenbaum, P. and Small, D. (2010). Using the cross-match test to appraise covariate balance in matched pairs. The American Statistician, 64, 299-309.

  • Baiocchi, M., Small, D., Lorch, S. and Rosenbaum, P. (2010). Building a stronger instrument in an observational study of perinatal care for premature infants. Journal of the American Statistical Association, 105, 1285-1296.

  • Small, D., Cheng, J. and Ten Have, T. (2010). Evaluating the efficacy of a malaria vaccine. International Journal of Biostatistics, Vol. 6 : Iss. 2, Article 4.

  • Heller, R., Jensen, S., Rosenbaum, P. and Small, D. (2010). Sensitivity analysis for the cross-match test with applications to genomics. Journal of the American Statistical Association, 105, 1005-1013.

  • Shirley, K., Small, D., Lynch, K., Maisto, S. and Oslin, D. (2010). Hidden markov models for alcoholism treatment trial data. Annals of Applied Statistics, 4, 366-395.

  • Lorch, S., Baiocchi, M., Even-Shoshan, O., Escobar, G., Silber, J. and Small, D. (2010). The role of outpatient facilities in explaining variations in risk-adjusted readmission rates between hospitals. Health Services Research, 45, 24-41.

  • Kunreuther, H., Silvasi, G., Bradlow, E. and Small, D. (2009). Bayesian analysis of deterministic and stochastic prisoner's dilemma games. Judgment and Decision Making, 4, 363-384.

  • Jensen, S., Erkan, I., Arnardottir, E. and Small, D. (2009). Bayesian testing of many hypotheses x many genes: a study of sleep apnea. Annals of Applied Statistics, 3, 1080-1101.

  • Zhang, K. and Small, D. (2009). Comment on "The esssential role of pair matching in cluster randomized experiments with application to the Mexican universal health insurance evaluation." Statistical Science, 24, 59-64.

  • Small, D. and Rosenbaum, P. (2009). Error free milestones in error prone measurements. Annals of Applied Statistics, 3, 881-901.

  • Heller, R., Rosenbaum, P. and Small, D. (2009). Split samples and design sensitivity in observational studies . Journal of the American Statistical Association, 104, 1090-1101.

  • Heller, R., Manduchi, E. and Small, D. (2009). Matching methods for observational microarray studies. Bioinformatics, 25, 904-909. Software

  • Gallop, R., Small, D., Lin, J., Elliott, M., Joffe, M. and Ten Have, T. (2009). Mediation analysis with principal stratification. Statistics in Medicine, 28, 1108-1130.

  • Small, D., Gastwirth, J., Krieger, A. and Rosenbaum, P. (2009). Simultaneous sensitivity analysis for observational studies using full matching or matching with multiple controls. Statistics and Its Interface, 2, 203-211. Data Set (Documentation).

  • Small, D. and Cheng. J. (2009). Discussion of "Identifiability and estimation of causal effects in randomized trials with noncompliance and completely nonignorable missing data." Biometrics, 65, 682-686.

  • Kurichi, J., Small, D., Bates, B., Prvu-Bettger, J., Kwong, P., Vogel, W.B., Bidelspach, D. and Stineman, M. (2009). Possible incremental benefits of specialized rehabilitation bed units among veterans following lower extremity amputation. Medical Care, 47, 457-465.

  • Cheng, J., Small, D., Tan, Z. and Ten Have, T. (2009). Efficient nonparametric estimation of causal effects in randomized trials with noncompliance. Biometrika , 96, 1-9.

  • Lai, T., Small, D. and Liu, J. (2009). Statistical inference in dynamic panel data models. Journal of Statistical Planning and Inference, 138, 2763-2776.

  • Entine, O. and Small, D. (2008). The role of rest in the NBA home court advantage . Journal of Quantitative Analysis in Sports, Vol 4: Iss. 2, Article 6.

  • Joffe, M., Small, D., Brunelli, S., Ten Have, T. and Feldman, H. (2008). Extended instrumental variables estimation for overall effects . International Journal of Biostatistics, Vol. 4: Iss. 1, Article 4.

  • Small, D. and Rosenbaum, P. (2008). War and wages: the strength of instrumental variables and their sensitivity to unobserved biases. Journal of the American Statisical Association, 103 924-933.

  • Small, D., Ten Have, T. and Rosenbaum, P. (2008). Randomization inference in a group randomized trial of treatments for depression: covariate adjustment, noncompliance and quantile effects. Journal of the American Statistical Association, 103, 271-279.

  • Small, D. (2007). Sensitivity analysis for instrumental variables regression with overidentifying restrictions. Journal of the American Statistical Association, 102, 1049-1058. Errata

  • Joffe, M., Small, D. and Hsu, C.-Y. (2007). Defining and estimating intervention effects for groups that will develop an auxiliary outcome . Statistical Science, 22, 74-97. Software. Link to journal

  • Lai, T. and Small, D. (2007). Marginal regression analysis of longitudinal data with time-dependent covariates: a generalized method of moments approach. Journal of the Royal Statistical Society, Series B, 69, 79-99. Software (corrected: 1/23/11)   (Documentation)  Data

  • Cheng, J. and Small, D. (2006). Bounds on causal effects in three-arm trials with noncompliance. Journal of the Royal Statistical Society, Series B, 68, 815-836. Software (Documentation).

  • Small, D., Gastwirth, J., Krieger, A. and Rosenbaum, P. (2006). R-Estimates vs. GMM: A theoretical case study of validity and efficiency. Statistical Science, 21, 363-375. Link to journal

  • Small, D., Ten Have, T., Joffe, M. and Cheng, J. (2006). Random effects logistic models for analysing efficacy of a longitudinal randomized treatment with non-adherence. Statistics in Medicine, 25, 1981-2007.

  • Apter, A., Cheng, J., Small, D., Bennett, I., Albert, C., Fein, D., George, M. and Van Horne, S. (2006). Asthma numeracy skill and health literacy. Journal of Asthma, 43, 705-710.

  • Chen, Y. and Small, D. (2005). Exact tests for the Rasch model via sequential importance sampling. Psychometrika, 70, 11-30.