Ken Kleinman, ScD

NIH-style Biographical Sketch

Full academic CV

Mailing Address: Harvard Medical School

Department of Ambulatory Care and Prevention

133 Brookline Avenue, 6th Floor

Boston, MA 02215

E-mail: Ken_Kleinman@hms.harvard.edu

Phone: (617) 509-9935

Fax: (617) 859-8112

Staff Assistant: Paul Guimond

Dr. Kleinman is an Associate Professor in the Department of Ambulatory Care and Prevention and is an applied biostatistician with diverse interests. He is involved with many projects at the DACP, including vaccine and bioterrorism surveillance, observational epidemiology, and individual-, practice-, and community-randomized interventions. He also provides statistical feedback on proposed studies for HPHC's research administration group. Dr. Kleinman also consults within the DACP and HPHC on various statistical issues and advises DACP fellows on statistical and methodological aspects of their research projects. His statistical research centers mainly on methods for clustered and longitudinal repeated measures data. He also has interests in the area of missing data methods. He is the author or co-author of over 100 peer-reviewed articles.

   My latest book, a bilingual dictionary showing how to do in R what you know how to do in SAS, and vice versa, is available to pre-order from Amazon!

Also, don't miss the book's web page, and our blog, with additional examples of how to do stuff in SAS and R.

Some interesting publications:

• Kleinman K, Ibrahim JG. A Semi-Parametric Bayesian Approach to the Random Effects Model. Biometrics 1998, v.54 921-938
• Kleinman K. Directed Double Data Entry: a Probabalistic Tool for Choosing Which Forms to Re-enter. Controlled Clinical Trials 2001 22 2-12
• Lazarus R, Kleinman K, Dashevsky I, Adams C, Kludt P, DeMaria A Jr, Platt R. Use of automated ambulatory-care encounter records for detection of acute illness clusters, including potential bioterrorism events. Emerg Infect Diseases 2002; 8(8):753-760. Available from: URL: http://www.cdc.gov/ncidod/EID/vol8no8/02-0239.htm
• Kleinman K, Lazarus R, Platt R. A Generalized Linear Mixed Models Approach for Detecting Incident Clusters of Disease in Small Areas, with an Application to Biological Terrorism (with invited Commentary) American Journal of Epidemiology 2004 159: 217-224 zip package with comment and response 365 kB
• Horton NJ and Kleinman KP. Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models. The American Statistician, 2007; 61(1):79-90 .pdf file 437 kb

Selected publications on public health surveillance:

• Kleinman K, Lazarus R, and Platt R. A generalized linear mixed models approach for detecting incident clusters of disease in small areas, with an application to biological terrorism. Am J Epidemiol. 2004;159(3):217-24 zip package with comment and response 365 kB
• Kleinman KP, Abrams AM, Kulldorff M, Platt R. A model-adjusted space-time scan statistic with an application to syndromic surveillance. Epidemiology and Infection 2005 119: 409-419 .pdf file 734kB
• Kleinman K, Abrams A, Yih WK, Platt R, Kulldorff M. Evaluating spatial surveillance: detection of known outbreaks in real data. Statistics in Medicine 2006; 25:755-769 .pdf file 235kB
• Kleinman KP, Abrams AM, Mandl KD, Platt R. Simulation for assessing statistical methods of bioterrorism surveillance. Morbidity and Mortality Weekly Report 2005 54 (supp.):101-108. .pdf file 934 kB
• Kleinman K, Abrams A. Assessing the utility of public health surveillance using specificity, sensitivity, and timeliness. Statistical Methods for Medical Research 2006 15:445-464 .pdf file  467kb
• Kleinman K, Abrams A. Assessing the utility of public health surveillance using specificity, sensitivity, and lives saved pdf 88kb

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