نتایج جستجو برای: instrumental measurement
تعداد نتایج: 468074 فیلتر نتایج به سال:
BACKGROUND Spatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological...
OBJECTIVE Alcohol price data collected by the American Chamber of Commerce Researchers Association (ACCRA) have been widely used in studies of alcohol consumption and related behaviors. A number of problems with these data suggest that they contain substantial measurement error, which biases conventional statistical estimators toward a finding of little or no effect of prices on behavior. We te...
Using instrumental variable methods to estimate the parameters of dynamic errors-in-variables systems with a periodic input signal is the focus in this report. How to choose suitable instrumental variable vectors is the key point. Four variants are proposed; all of them can generate consistent estimates. An analysis shows that the best accuracy is achieved by using a specific overdetermined ins...
Instrumental variables (IV) estimators are well established to correct for measurement error on exposure in a broad range of fields. In a distinct prominent stream of research IV's are becoming increasingly popular for estimating causal effects of exposure on outcome since they allow for unmeasured confounders which are hard to avoid. Because many causal questions emerge from data which suffer ...
This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T → 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables...
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