Web Surveys

• Schonlau M., Van Soest A, Kapteyn A, Couper M. Selection bias in Web surveys and the use of propensity scores. (to appear Feb 2009) Sociological Methods and Research. SSRN Link
• Schonlau M., Van Soest A, Kapteyn A, Are `Webographic' or attitudinal questions useful for adjusting estimates from Web surveys using propensity scoring? Survey Research Methods, 2007; 1(3): 155-163. (pdf)
• Schonlau M., Van Soest A, Couper M, Winter J, Kapteyn . Attempting to adjust for selection bias in Web surveys with propensity scores: the case of the Health and Retirement Survey (HRS). In Proceedings of the Section on Survey Statistics, American Statistical Association; 2004, CD-ROM. (pdf)
• Couper M, Kapteyn A, Schonlau M, Winter J. Noncoverage and Nonresponse in an Internet Survey. Social Science Research. 2007; 36:131-148.
• Schonlau M. Will web surveys ever become part of mainstream research? Journal of Medical Internet Research. 2004; 6(3):e31. (pdf on www.jmir.org)
• Schonlau M, Zapert K, Payne Simon L, Sanstad K, Marcus S, Adams J, Spranca M, Kan H-J, Turner R, Berry S. A comparison between a propensity weighted web survey and an identical RDD survey. Social Science Computer Review. 2004; 22(1): 128-138. (pdf)
• Schonlau M, Asch BJ, Du C. "Web surveys as part of a mixed mode strategy for populations that cannot be contacted by e-mail." Social Science Computer Review. 2003; 21(2):218-222. (pdf)
• Schonlau, M., Fricker R., Elliott, M. "Conducting Research Surveys via E-Mail and the Web", RAND, Santa Monica, CA. 2002.
  This book is available on Amazon.com and at the RAND web site for this book.
  Book Reviews and Recommendations
• Fricker R, Schonlau M. "Advantages and disadvantages of Internet research surveys: Evidence from the literature." Field Methods. 2002;14(4):347-367. (pdf)

Data Mining

• Schonlau M. Boosted Regression (Boosting): An introductory tutorial and a Stata plugin. The Stata Journal, 2005; 5(3):330-354. (pdf)
• Raghavan N., Bell R., Schonlau M., Pregibon D., Karr A.. (2000). "Defection detection: Using online activity profiles to predict ISP customer vulnerability" in Proceedings: The Sixth International Conference of Knowledge Discovery and Data Mining, August , Boston, 506-515. (pdf)

Visualization / Graphics

• Schonlau M. Visualizing Categorical Data Arising in the Health Sciences Using Hammock Plots. In Proceedings of the Section on Statistical Graphics, American Statistical Association; 2003, CD-ROM. (pdf)
• Schonlau, M. Visualizing Hierarchical and Non-Hierarchical Cluster Analyses with Clustergrams. Computational Statistics: 2004; 19(1): 95-111. (pdf)
• Schonlau M. "The clustergram: a graph for visualizing hierarchical and non-hierarchical cluster analyses." The Stata Journal, 2002; 2 (4):391-402. (pdf)
• Schonlau, M., Hamada, M., Welch, W. (1995). ``Nonparametric Function-Fitting To Suggest Nonlinear Parametric Models''. American Statistical Association Proceedings, Section of Physical Engineering Sciences, 262-267 (pdf)

Criminology

• Schonlau, M. Charging Decisions in Death-Eligible Federal Cases (1995-2000): Arbitrariness, Capriciousness, and Regional Variation in: Klein , Berk and Hickman (editors) Race and the Decision to Seek the Death Penalty in Federal Cases. RAND Corporation, 2006, TR-389-NIJ.
RAND website (see chapter 4 in pdf)

Health Sciences

• Miller DC, Schonlau M, Litwin MS, Lai J, Saigal CS, and the Urologic Diseases in America Project. Renal and Cardiovascular Morbidity After Partial or Radical Nephrectomy, Cancer, Feb 1 2008; 112(3): 511-521.
• Schonlau M, Mangione-Smith R, Rosen M, Chan K, Louis T, Wu S, Keeler E. An evaluation of an adult asthma BTS collaborative and the effect of patient self-management, Annals of Family Medicine. Ann Fam Med 2005 3: 200-208. (pdf on www.annfammed.org)
• Chan K, Keeler E, Schonlau M, Rosen M, Mangione-Smith R. How do Ethnicity and Primary Language Spoken at Home Affect Management Practices and Outcomes in Children with Asthma? Archives of Pediatric and Adolescent Medicine. 2005; 159 (Mar): 283-289.
• Mangione-Smith R, Schonlau M, Rosen M, Chan K, Louis T, Keeler E. Measuring the Effectiveness of a Collaborative for Quality Improvement in Pediatric Asthma Care: Does Implementing the Chronic Care Model Improve Processes and Outcomes of Care? Ambulatory Pediatrics. 2005; 5 (2): 75-82.
• Goldman D, Berry S, McCabe M, Kilgore M, Potosky A, Schoenbaum M, Schonlau M, Weeks J, Kaplan R, Escarce J. Incremental Treatment Costs in NCI- Sponsored Clinical Trials, JAMA. 2003; 289(22): 2970-2977.
• Lewis JH, Schonlau M, Muñoz J, Asch SM, Rosen MR, Yang H, Escarce JJ. Pharmacy Compliance With California's Prescription Drug Discount Program for Medicare Beneficiaries. The New England Journal of Medicine. 2002;346(11):830-835. (pdf)
• Adams JL, Schonlau M, Escarce J, Kilgore M, Schoenbaum M, Goldman DP. Sampling Patients Within and Across Health Care Providers: Multi-Stage Non-nested Samples in Health Services Research. Health Services and Outcomes Research Methodology. 2003; 4(3): 151-167. (pdf)

Computer Experiments / Global Optimization

• Schonlau M., Welch WJ. Screening the Input Variables to a Computer Code Via Analysis of Variance and Visualization. In Screening: Methods for Experimentation in Industry, Drug Discovery and Genetics. Eds: A. M. Dean and S. M. Lewis, Springer Verlag, New York; 2006:308-327.
• Jones, D., Schonlau, M., Welch, W., (1998) ``Efficient Global Optimization of Expensive Black-Box Functions''. Journal of Global Optimization} Vol. 13, 455-492. (pdf)
• Schonlau, M., Welch, W., Jones, D. (1998), "Global Versus Local Search in Constrained Optimization of Computer Models," in New Developments and Applications in Experimental Design, N. Flournoy, W.F. Rosenberger, and W.K. Wong (editors), Institute of Mathematical Statistics, Hayward, California, Vol. 34, 11-25. (pdf)
• Mrawira, D., Welch, W., Schonlau, M., Haas, R. (1999) "Sensitivity Analysis of Computer Models: The World Bank HDM-III Model" Journal of Transportation Engineering, 421-428. (pdf) (Figure 2 pdf)
• Schonlau, M., Welch, W., Jones, D. (1997) ``A Data-Analytic Approach to Bayesian Global Optimization'' . American Statistical Association Proceedings, Section of Physical Engineering Sciences, 186-191. (pdf)
• Matthias Schonlau (1997). "Computer Experiments and Global Optimization" Ph.D. Dissertation, University of Waterloo. (1.1 MB, approx 130 pages, (pdf)
• Schonlau, M., Welch, W. (1996). ``Global Optimization with Nonparametric Function Fitting''. Proceedings of the Section on Physical and Engineering Sciences}, American Statistical Association, 183-186. (pdf)
• Welch, W.J, Buck, R.J., Sacks, J., Wynn, H.P., Mitchell, T.J., Morris, M.D., Schonlau, M. (1996), Rejoinder to ``Comments on Computer Experiments'' by James M. Lucas, Technometrics, 38,199-203. (pdf)

Computer intrusion detection/ Counter Terrorism

• Stoto M , Schonlau M., Mariano L. Syndromic Surveillance : Is it Worth the Effort? Chance. 2004: 17, 1, 19-24.
• Schonlau, M., DuMouchel, W., Ju, W., Karr, A., Theus, M., Vardi, Y. (2001), "Computer Intrusion: Detecting Masquerades," Statistical Science, 2001;16(1):58-74. (pdf)
  Note 1 : Some of the figures at the end are in color .
  Note 2 : The pdf reader may display a warning "Less data read than expected" with this file - the file has 39 pages and is complete.
• Schonlau, M., Theus, M. (2000), "Detecting Masquerades in Intrusion Detection Based on Unpopular Commands," Information Processing Letters, 76, 33-38. (pdf)
• Theus, M., Schonlau, M., 1998, ``Intrusion Detection Based on Structural Zeroes''.  Statistical Computing & Graphics Newsletter. Vol. 9, No 1, 12 - 17. (pdf)
• DuMouchel, W., Schonlau, M., ``A fast computer intrusion detection algorithm based on hypothesis testing of command transition probabilities''.  The Fourth International Conference of Knowledge Discovery and Data Mining, August 27-31, New York, pp. 189-193. (pdf)
• DuMouchel, W., Schonlau, M. (1999), "A Comparison of Test Statistics for Computer Intrusion Detection Based on Principal Components Regression of Transition Probabilities," Proceedings of the 30th Symposium on the Interface: Computing Science and Statistics, 30, 404-413. (pdf)