کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10514347 950975 2010 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی سیاست های بهداشت و سلامت عمومی
پیش نمایش صفحه اول مقاله
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
چکیده انگلیسی
Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Clinical Epidemiology - Volume 63, Issue 8, August 2010, Pages 826-833
نویسندگان
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