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Comparison of the Inverse Probability of Treatment Weighted (IPTW) Estimator With a Naïve Estimator in the Analysis of Longitudinal Data With Time-Dependent Confounding: A Simulation Study

机译:时变混杂纵向数据分析中处理加权(IPTW)估计与天真估计的逆概率比较:模拟研究

摘要

A simulation study was conducted to compare estimates from a naïve estimator, using standard conditional regression, and an IPTW (Inverse Probability of Treatment Weighted) estimator, to true causal parameters for a given MSM (Marginal Structural Model). The study was extracted from a larger epidemiological study (Longitudinal Study of Effects of Physical Activity and Body Composition on Functional Limitation in the Elderly, by Tager et. al [accepted, Epidemiology, September 2003]), which examined the causal effects of physical activity and body composition on functional limitation. The simulation emulated the larger study in terms of the exposure and outcome variables of interest-- physical activity (LTPA), body composition (LNFAT), and physical limitation (PF), but used one time-dependent confounder (HEALTH) to illustrate the effects of estimating causal effects in the presence of time-dependent confounding. In addition to being a time-dependent confounder (i.e. predictor of exposure and outcome over time), HEALTH was also affected by past treatment. Under these conditions, naïve estimates are known to give biased estimates of the causal effects of interest (Robins, 2000). The true causal parameters for LNFAT (-0.61) and LTPA (-0.70) were obtained by assessing the log-odds of functional limitation for a 1-unit increase in LNFAT and participation in vigorous exercise in an ideal experiment in which the counterfactual outcomes were known for every possible combination of LNFAT and LTPA for each subject. Under conditions of moderate confounding, the IPTW estimates for LNFAT and LTPA were -0.62 and -0.94, respectively, versus the naïve estimates of -0.78 and -0.80. For increased levels of confounding of the LNFAT and LTPA variables, the IPTW estimates were -0.60 and -1.28, respectively, and the naïve estimates were -0.85 and -0.87. The bias of the IPTW estimates, particularly under increased levels of confounding, was explored and linked to violation of particular assumptions regarding the IPTW estimation of causal parameters for the MSM.
机译:进行了模拟研究,以比较标准条件回归和朴素估计量的估计以及IPTW(治疗加权加权的逆概率)估计量与给定MSM(边际结构模型)的真实因果参数之间的比较。该研究摘自一项较大的流行病学研究(纵向运动对身体活动和身体成分对老年人功能限制的影响的研究,由Tager等人接受[流行病学,2003年9月]),该研究考察了身体活动的因果关系和身体成分对功能的限制。该模拟在关注的暴露和结果变量方面进行了较大的研究-身体活动(LTPA),身体成分(LNFAT)和身体限制(PF),但是使用了一个时间依赖性混杂因素(HEALTH)来说明在存在时间依赖性混淆的情况下估计因果效应的影响。除了作为时间依赖的混杂因素(即随着时间推移暴露和结果的预测因素)外,健康还受到过去治疗的影响。在这种情况下,已知幼稚的估计会给出感兴趣的因果效应的有偏估计(Robins,2000)。 LNFAT(-0.61)和LTPA(-0.70)的真正因果参数是通过评估LNFAT增加1个单位并参加剧烈运动的功能极限的对数奇数来获得的对于每个主题的LNFAT和LTPA的每种可能组合都知道。在中等程度混杂的条件下,LNFAT和LTPA的IPTW估计分别为-0.62和-0.94,而单纯的估计为-0.78和-0.80。对于LNFAT和LTPA变量的混杂程度提高,IPTW估计分别为-0.60和-1.28,而朴素的估计为-0.85和-0.87。探究了IPTW估计的偏见,尤其是在混杂水平提高的情况下,并与违反有关IPTW估计MSM因果参数的特定假设相违背。

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