Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
Top Cited Papers
- 1 August 2010
- journal article
- review article
- Published by Elsevier BV in Journal of Clinical Epidemiology
- Vol. 63 (8), 826-833
- https://doi.org/10.1016/j.jclinepi.2009.11.020
Abstract
No abstract availableFunding Information
- University of North Carolina at Chapel Hill Center for AIDS Research (CFAR) (#P30 AI50410)
- UNC-GlaxoSmithKline Center for Excellence in Pharmacoepidemiology and Public Health
- UNC School of Public Health
- NIH/NIAID (5 T32 AI 07001-31)
This publication has 36 references indexed in Scilit:
- Improving propensity score weighting using machine learningStatistics in Medicine, 2010
- COBEpro: a novel system for predicting continuous B-cell epitopesProtein Engineering, Design and Selection, 2008
- Evaluating uses of data mining techniques in propensity score estimation: a simulation studyPharmacoepidemiology and Drug Safety, 2008
- Using Clinical Classification Trees to Identify Individuals at Risk of STDs During PregnancyPerspectives on Sexual and Reproductive Health, 2007
- Variable Selection for Propensity Score ModelsAmerican Journal of Epidemiology, 2006
- Indications for Propensity Scores and Review of their Use in PharmacoepidemiologyBasic & Clinical Pharmacology & Toxicology, 2006
- Kernel Logistic Regression and the Import Vector MachineJournal of Computational and Graphical Statistics, 2005
- Support vector machines for spam categorizationIEEE Transactions on Neural Networks, 1999
- Neural Networks for Pattern Recognition.Journal of the American Statistical Association, 1997
- The central role of the propensity score in observational studies for causal effectsBiometrika, 1983