Interpretation of logistic regression and propensity score analysis
نویسندگان
چکیده
منابع مشابه
Systematic differences in treatment effect estimates between propensity score methods and logistic regression.
BACKGROUND In medical research both propensity score methods and logistic regression analysis are used to estimate treatment effects in observational studies. From literature reviews it has been concluded that treatment effect estimates from both methods are quite similar. With this study we will show that there are systematic differences which can be substantial. METHODS We used a simulated ...
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The covariate-balancing propensity score (CBPS) extends logistic regression to simultaneously optimize covariate balance and treatment prediction. Although the CBPS has been shown to perform well in certain settings, its performance has not been evaluated in settings specific to pharmacoepidemiology and large database research. In this study, we use both simulations and empirical data to compar...
متن کاملpropensity score analysis
Methods for propensity score analysis (PSA) originated with Rosenbaum and Rubin (1983), as vehicles to sharpen and clarify treatment group comparisons in observational studies. Although highly recommended by many statisticians, and applied often in medical sciences, PSA has seen relatively few applications in the social and behavioral sciences. This paper aims to facilitate sound PSA applicatio...
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Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods : In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were ...
متن کاملComparison of logistic regression versus propensity score when the number of events is low and there are multiple confounders.
The aim of this study was to use Monte Carlo simulations to compare logistic regression with propensity scores in terms of bias, precision, empirical coverage probability, empirical power, and robustness when the number of events is low relative to the number of confounders. The authors simulated a cohort study and performed 252,480 trials. In the logistic regression, the bias decreased as the ...
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ژورنال
عنوان ژورنال: Tenri Medical Bulletin
سال: 2016
ISSN: 1344-1817,2187-2244
DOI: 10.12936/tenrikiyo.19-008