Schafer, Daniel W.
Statistics
Department
Kidder Hall 44
Oregon State University
Corvallis, Oregon 97331-4606
Voice: (541) 737-1990; FAX: (541) 737-3489;
E-mail: schafer AT science DOT oregonstate DOT edu
Office: Kidder Hall, Room 58
Education
Pomona
College 1974-78 B.A. 1978
Mathematics
University of Chicago 1978-81
M.S. 1981 Statistics
University of Chicago 1981-82
PhD. 1982 Statistics
Academic Interests:
Statistical Education.
Statistical Methodology for Studying Health Effects of Low Doses of Radiation.
Statistical Methodology for Regression with Measurement Errors in Explanatory Variables
Selected Publications:
1. Ramsey,
F. L. and Schafer, D. W. (2002) The Statistical Sleuth, A Course
in Methods of Data Analysis , Second Edition, Belmont, CA: Duxbury Press.
2. Schafer,
D. S. and F. L. Ramsey (2003), Teaching the craft of data analysis
, Journal of Statistical Education,.Vol. 11.
3. Schafer, D.W. and Gilbert, E. S. (2006) Some statistical implications of dose uncertainty in radiation dose-response analyses, Radiation Research, 155, 303-312.
4. Health Risks from Exposure to Low Levels of Ionizing Radiation: BEIR VII Phase 2 (2006) (one of many authors, National Academy of Science BEIR VII Committee).
5. Lubin, J. H., D. W. Schafer, E. Ron, M. Stovall, and R. J. Carroll, (2004) A Reanalysis of thyroid neoplasms in the Israeli tinea capitis study accounting for dose uncertainties, Radiation Research, 161, 359-368.
6. Schafer, D. W., J. H. Lubin, E. Ron, M. Stovall, and R. J. Carroll, (2001)
Thyroid cancer following scalp irradiation: a reanalysis accounting for uncertainty in dosimetry, Biometrics. 57, 689-697.
7. Schafer, D.W., L.A. Stefanski, and R. J. Carroll, (1999) Consideration of measurement errors in the international radiation study of cervical cancer, in Uncertainties in Radiation Dosimetry and Their Impact on Dose-Response Analyses, Ron, E. and F. O. Hoffman eds. National Institutes of Health Publication 99-4541.
8.Pierce, D. A., D. O. Stram, M. Vaeth, and D. W. Schafer (1992) The errors-in-variables problem: considerations provided by radiation dose-response analyses of the A-bomb survivor data, Journal of the American Statistical Association, 87, 351-359
9. Suh, E. and D. W. Schafer (2002),Semiparametric maximum likelihood for nonlinear regression with measurement errors, Biometrics, 58, 448-453.
10. Schafer, D. W., (2002) Likelihood analysis and flexible structural modeling for measurement error model regression, Journal of Statistical Computation and Simulation, 72, 33-46.
11. Higdon, R. and Schafer, D. W. (2002), Likelihood analysis and flexible structural modeling for measurement error model regression, Journal of Statistical Computing and Data Analysis 35, 283-299.
12. Schafer, D. W. (2001) Semiparametric maximum likelihood for measurement error model regression, Biometrics, 57, 53-61.
Doctoral Students:
- Lisa Ganio - Diagnostic
tools for overdispersion in generalized models. 1990.
- Roger Sauter - A method
for estimation of generalized linear models when explanatory variables
contain measurement error. 1990.
- James Pratt - The Laplace
approximation and inference in generalized linear models with two or more
random effects. 1995.
- James Kolsky - Extensions
for paired comparisons models. 1996.
- Roger Higdon – Likelihood
analysis for regression with measurement errors. 1998.
- Eun-Young Suh –
Semiparametric maximum likelihood for measurement error model
regression. 2001.
- Vicente Monleon – Regression Calibration Inference With Calibration Data. 2006.
- Yonghai Li - Multivariate Ordinal Probit Regression for Repeated, Ordered Categorical Responses. 2008.
- Jack Giovannini - Ordered Response Regression for Wildlife Reproductive Success Studies. 2008.
Positions, etc.:
Fellow of the American Statistical Association, past President of the Oregon Chapter of the American Statistical Association, former Associate Editor of The American Statistician, former interim Chairman of the Statistics Department of Oregon State University
Other Interests:
University of Chicago 1978-81 M.S. 1981 Statistics
University of Chicago 1981-82 PhD. 1982 Statistics
Selected Publications:
1. Ramsey,
F. L. and Schafer, D. W. (2002) The Statistical Sleuth, A Course
in Methods of Data Analysis , Second Edition, Belmont, CA: Duxbury Press.
2. Schafer, D. S. and F. L. Ramsey (2003), Teaching the craft of data analysis , Journal of Statistical Education,.Vol. 11.
3. Schafer, D.W. and Gilbert, E. S. (2006) Some statistical implications of dose uncertainty in radiation dose-response analyses, Radiation Research, 155, 303-312.
4. Health Risks from Exposure to Low Levels of Ionizing Radiation: BEIR VII Phase 2 (2006) (one of many authors, National Academy of Science BEIR VII Committee).
5. Lubin, J. H., D. W. Schafer, E. Ron, M. Stovall, and R. J. Carroll, (2004) A Reanalysis of thyroid neoplasms in the Israeli tinea capitis study accounting for dose uncertainties, Radiation Research, 161, 359-368.
6. Schafer, D. W., J. H. Lubin, E. Ron, M. Stovall, and R. J. Carroll, (2001) Thyroid cancer following scalp irradiation: a reanalysis accounting for uncertainty in dosimetry, Biometrics. 57, 689-697.
7. Schafer, D.W., L.A. Stefanski, and R. J. Carroll, (1999) Consideration of measurement errors in the international radiation study of cervical cancer, in Uncertainties in Radiation Dosimetry and Their Impact on Dose-Response Analyses, Ron, E. and F. O. Hoffman eds. National Institutes of Health Publication 99-4541.
8.Pierce, D. A., D. O. Stram, M. Vaeth, and D. W. Schafer (1992) The errors-in-variables problem: considerations provided by radiation dose-response analyses of the A-bomb survivor data, Journal of the American Statistical Association, 87, 351-359
9. Suh, E. and D. W. Schafer (2002),Semiparametric maximum likelihood for nonlinear regression with measurement errors, Biometrics, 58, 448-453.
10. Schafer, D. W., (2002) Likelihood analysis and flexible structural modeling for measurement error model regression, Journal of Statistical Computation and Simulation, 72, 33-46.
11. Higdon, R. and Schafer, D. W. (2002), Likelihood analysis and flexible structural modeling for measurement error model regression, Journal of Statistical Computing and Data Analysis 35, 283-299.
12. Schafer, D. W. (2001) Semiparametric maximum likelihood for measurement error model regression, Biometrics, 57, 53-61.
Doctoral Students:
- Lisa Ganio - Diagnostic tools for overdispersion in generalized models. 1990.
- Roger Sauter - A method for estimation of generalized linear models when explanatory variables contain measurement error. 1990.
- James Pratt - The Laplace approximation and inference in generalized linear models with two or more random effects. 1995.
- James Kolsky - Extensions for paired comparisons models. 1996.
- Roger Higdon – Likelihood analysis for regression with measurement errors. 1998.
- Eun-Young Suh – Semiparametric maximum likelihood for measurement error model regression. 2001.
- Vicente Monleon – Regression Calibration Inference With Calibration Data. 2006.
- Yonghai Li - Multivariate Ordinal Probit Regression for Repeated, Ordered Categorical Responses. 2008.
- Jack Giovannini - Ordered Response Regression for Wildlife Reproductive Success Studies. 2008.
Positions, etc.:
Fellow of the American Statistical Association, past President of the Oregon Chapter of the American Statistical Association, former Associate Editor of The American Statistician, former interim Chairman of the Statistics Department of Oregon State University
Other Interests: