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Estimation of propensity score using spatial logistic regression

机译:使用空间逻辑回归估计倾向分数

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Propensity score is a method used to reduce bias due to confounding factors in the estimation of the treatment impact on observational data.Propensity score is the conditional probability to get certain treatments involving the observed covariates.In general, propensity score can be calculated using two methods, they are logistic regression and Classification and Regression Tree Analysis(CART).Logistic regression model is the most common method used.In which, logistic regression model is a model used to estimate the probability of an event.In other side, collecting data by observing many subjects in different place will be influenced spatial effect.Thus, this paper will estimate propensity score using spatial logistic regression.
机译:倾向评分是一种方法,用于减少偏差导致偏差导致估计对观察数据的治疗影响的影响。分数是获得涉及观察到的协变量的某些治疗的条件概率。一般来说,可以使用两种方法计算倾向评分,它们是逻辑回归和分类和回归树分析(推车).Logistic回归模型是最常用的方法。在哪个中,Logistic回归模型是用于估计事件概率的模型。在其他方面,收集数据观察不同地方的许多科目将受到空间效应。本文将使用空间逻辑回归估算倾向分数。

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