Monotonic Dichotomous Regression Estimates: A Burn Care Example

Wolfe, Robert A.; Roi, Larry D.; Margosches, Elizabeth

doi:10.2307/2530533

Cited by 3 publications

(1 citation statement)

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“…The probability of developing lung cancer is thought to be an increasing function of cigarettes smoked per day (Morabia and Wynder, 1991). The probability of death is assumed to be a monotone function of the severity of burn injury (Wolfe, Roi, and Margosches, 1981). A dose response curve is often assumed to be non-decreasing (Bhattacharya and Kong, 2007, Dette et al, 2005, Müller and Schmitt, 1988, Park and Park, 2006.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Parametric and Nonparametric Estimates of the Attributable Fraction for a Semi-continuous Exposure

Wang¹,

Small²

2012

The International Journal of Biostatistics

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The attributable fraction of a disease due to an exposure is the fraction of disease cases in a population that can be attributed to that exposure. We consider the attributable fraction for a semicontinuous exposure, that is an exposure for which a clump of people have zero exposure and the rest of the people have a continuously distributed positive exposure. Estimation of the attributable fraction involves estimating the conditional probability of having the disease given the exposure. Three main approaches to estimating the probability function are (1) a classical method based on sample averages; (2) parametric regression methods such as logistic regression models and power models; and (3) nonparametric regression methods including local linear smoothing and isotonic regression. We compare performance of these methods in estimating the attributable fraction for a semi-continuous exposure in a simulation study and in an example.

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