JEROME P. REITER
Mrs. Alexander Hehmeyer Associate Professor of Statistical Science
Department of Statistical Science
Duke University
General research papers on multiple imputation for missing data, survey methodology, and causal inference
1. Reiter, J.
P. (2000)
"Using statistics to determine causal
relationships,"
The American Mathematical Monthly, 107,
24-32.
2. Hill, J. L., Reiter, J.
P., Zanutto, E.
(2004) "A comparison of
experimental
and observational data analyses," In
Applied Bayesian Modeling and Causal
Inference from Incomplete-Data Perspectives, edited
by A. Gelman and X. Meng. New York: Wiley, 49 - 60.
3. Reiter,
J.,
Zanutto, E., and
Hunter, L. (2005) "Analytical
modeling in complex surveys of work practices," Industrial
Labor Relations Review, 59, 82-100.
4. Hill,
J. L. and Reiter, J. P. (2006) "Interval estimation of treatment
effects when using propensity score matching,"
Statistics in Medicine, 25:13,
2230 - 2256
.
5. Reiter, J. P.,
Raghunathan, T. E., and Kinney, S. (2006),
"The importance of modeling the sampling design in multiple
imputation
for missing data,"
Survey
Methodology, 32.2, 143 - 150
.
6. Reiter, J. P.
(2007), "Small-sample degrees
of
freedom for multi-component
significance tests with multiple imputation for missing data,"
Biometrika, 94, 502 - 508
.
7. Reiter, J.
P.
(2008), "Multiple imputation when records used for imputation
are not used or disseminated for analysis,"
Biometrika, 95, 933 - 946.
8. Woo, M. J., Reiter, J. P., and Karr, A. F. (2008), "Estimation of propensity
scores using generalized additive models,"
Statistics in
Medicine, 27, 3806 - 3816.
9. Kinney, S. K. and Reiter, J. P. (2009), "Inferences for
two stage multiple imputation for nonresponse,"
Journal of
Statistical Theory and Practice, 3, 307 - 318.
10. Marchenko, Y. V. and Reiter, J. P. (2009) "Improved
degrees of freedom for multivariate significance tests obtained
from multiply-imputed, small sample data,"
The
Stata Journal, 9, 388 - 397.
11. Zhou, X. and Reiter, J. P. (forthcoming) "A note on Bayesian inference after multiple imputation,"
The American Statistician.