Dr. Ratcliffe's statistical methodological research focuses on functional data analysis (models for complex curves), and the analysis of longitudinal data with informative dropout, particularly joint models for longitudinal and survival data. Her collaborative areas of interest include reproductive and women’s health, HIV/AIDS and sleep research. Research projects include modeling of changes in sleep and body composition through the menopausal transition, and modeling of labor progression.
Dr. Ratcliffe is MPI of an NIH funded research grant on Semi-parametric joint models for longitudinal and time to event data. A postdoctoral fellowship is currently available on this grant. See the Penn medicine biomedical postdoctoral jobs for more information.
- Matlab programs from: Ratcliffe SJ, Guo G and Ten Have TR. Joint modelling of longitudinal and survival data via a common frailty. Biometrics, 60(4):892-899, 2004
- Matlab programs from: Guo W, Ratcliffe SJ and Ten Have TR. A Random pattern-mixture model for longitudinal data with dropouts. Journal of the American Statistical Association, 99:929-937, 2004.
- Matlab programs from: Ratcliffe SJ and Shults J. GEEQBOX: A Matlab toolbox for generalized estimating equations and quasi-least squares. Journal of Statistical Software, 25(14):1-14, 2008.
A complete list of published work is available in MyBibliography, Google Scholar, and Research Gate
- Liu C, Ratcliffe SJ and Guo W. A Random pattern mixture model for ordinal outcomes with informative dropouts. Statistics in Medicine, 2015 Apr 20. [Epub ahead of print]
- Elmi A, Ratcliffe SJ, and Guo W. The estimation of branching curves in the presence of subject-specific random effects. Statistics in Medicine, 33(29):5166-76, 2014. [Epub: 2014 Sep 4]
- Harhay MO, Wagner J, Ratcliffe SJ, Bronheim RS, Gopal A, Green S, Cooney E, Mikkelsen ME, Kerlin MP, Small DS, and Halpern SD. Outcomes and statistical power in adult critical care randomized trials. American Journal of Respiratory and Critical Care Medicine, 189(12):1469-78, 2014. [Epub 2014 Apr 30]
- Brown SES, Ratcliffe SJ, and Halpern SD. An empirical comparison of key statistical attributes among potential intensive care unit quality indicators. Critical Care Medicine, 42(8):1821-31, 2014. [Epub 2014 Apr 8]
- Elmi A, Ratcliffe SJ, Parry S, and Guo W. A B-spline based semiparametric nonlinear mixed effects model. Journal of Computational and Graphical Statistics, 20(2):492-509, 2011. [Epub: 2011 Mar 23]
- Shults J and Ratcliffe SJ. Methods research on a limited budget. In: Glickman ME, Ittenbach RF, Nick TG, O’Brien RG, Ratcliffe SJ, and Shults J. Statistical Consulting with Limited Resources: Applications to Practice. Chance, 23(4):35-42, 2010.
- Shults J, and Ratcliffe SJ. Analysis of multi-level correlated data in the framework of generalized estimating equations via xtmultcorr procedures in Stata and qls functions in Matlab. Statistics and its Interface, 2:187-196, 2009.
- Ratcliffe SJ and Shults J. GEEQBOX: A Matlab toolbox for generalized estimating equations and quasi-least squares. Journal of Statistical Software, 25(14):1-14, 2008.
- Shults J, Ratcliffe SJ, and Leonard M. Improved generalized estimating equation analysis via xtqls for implementation of quasi-least squares in Stata. The Stata Journal, 7(2):147-166, 2007.
- Sammel MD, Ratcliffe SJ, and Leiby BE. Factor analysis. In Chow S-C (ed), Encyclopedia of Biopharmaceutical Statistics, 2nd Edition, Marcel Dekker Inc., New York, 2006.
- Ratcliffe SJ, Guo G, and Ten Have TR. Joint modeling of longitudinal and survival data via a common frailty. Biometrics, 60(4):892-9, 2004.
- Guo W, Ratcliffe SJ, and Ten Have TR. A Random pattern-mixture model for longitudinal data with dropouts. Journal of the American Statistical Association, 99: 929-937, 2004.
- Ten Have TR, Ratcliffe SJ, Reboussin BA, Kunselman A, and Miller ME. Deviations from the population-averaged versus subject-specific relationship for clustered binary data. Statistical Methods in Medical Research, 13(1):3-16, 2004.
- Ratcliffe SJ, Heller GZ, and Leader LR. Functional data analysis with application to periodically stimulated fetal heart rate data: II. Functional logistic regression. Statistics in Medicine, 21:1115-27, 2002.
- Ratcliffe SJ, Leader LR, and Heller GZ. Functional data analysis with application to periodically stimulated fetal heart rate data: I. Functional regression. Statistics in Medicine, 21:1103-14, 2002.
- Sammel MD, Wang Y, Ratcliffe SJ, Freeman E, and Propert KJ. Models for within subject heterogeneity as a risk factor for disease. 2001 Proceedings of the American Statistical Association, Biometrics Section, [CD-ROM], 2001.
- Ratcliffe SJ and Solo V. Functional mean and covariance modelling. In American Statistical Association: 1999 Proceedings of the Statistical Computing Section. pp. 206-209, 1999.
- Ratcliffe SJ and Solo V. Some issues in functional principal component analysis. In American Statistical Association: 1998 Proceedings of the Statistical Computing Section. pp.119-124, 1998.
Biostatistics Ph.D. Students
- Angelo F. Elmi. "Curve registration in functional data analysis with informatively censored event-times." Graduated 2009.
- ChengCheng Liu. "Joint modeling of non-gaussian longitudinal outcomes and time to event data." Graduated 2011.
- Arwin Thomasson. "Joint longitudinal-survival model with possible cure: An analysis of patient
outcomes on the liver transplant waiting list." Graduated 2012.
Epidemiology Ph.D. Students
- Sydney E.S. Brown. "The epidemiology of readmissions to the intensive care unit and its use as a quality indicator." Graduated 2013. Dissertation available from ProQuest
- Michael Harhay. Research focuses on design and analysis issues encountered in intensive care unit-based clinical trials