Tarter M E, Lock M D, Ray R M
Department of Biomedical and Environmental Health Sciences, University of California, Berkeley 94720, USA.
Environ Health Perspect. 1995 Jul-Aug;103(7-8):748-55. doi: 10.1289/ehp.95103748.
We introduce a new form of regression that has many applications to environmental studies. For a sequence composed of key variates with prototypic value chi, this form differs from the estimation of a location parameter-based curve, mu(chi), a scale parameter-based curve, sigma(chi), or other currently used types of regression. Instead of estimating a curve location, scale, or alpha-quantile parameter, it assumes that there are two or more population subgroups; for example, consisting of unsensitized and sensitized individuals, respectively. Although within each subgroup the relationships mu(chi) or sigma(chi) may or may not be horizontal, these relationships are not deemed to be of primary importance. Instead, the mixing parameter P that indexes the proportions of the two subgroups is treated as being related to the key variate value chi. In the sense that its goal is the estimation of a proportion, the new procedure resembles logit regression. But, in terms of the continuous spectrum of values attained by the response variate, the means used to attain its goal are dissimilar from those of logit regression. Specifically, group membership is not known directly but is determined from a proxy continuous variate whose values overlap between groups. Examples are given with simulated and natural data where this new form of regression is applied. We believe that conditional switching regression is a particularly valuable research tool when chemical level chi of an induced asthma attack or birthweight chi measured in a study of the biomarker cotinine's effect on pregnancy outcomes determines whether an attack or a negative outcome occurs.(ABSTRACT TRUNCATED AT 250 WORDS)
我们引入了一种新的回归形式，它在环境研究中有许多应用。对于由具有原型值χ的关键变量组成的序列，这种形式不同于基于位置参数的曲线μ(χ)、基于尺度参数的曲线σ(χ)或其他当前使用的回归类型的估计。它不是估计曲线的位置、尺度或α分位数参数，而是假设存在两个或更多总体亚组；例如，分别由未致敏和致敏个体组成。尽管在每个亚组内，μ(χ)或σ(χ)的关系可能是水平的，也可能不是水平的，但这些关系并不被认为是最重要的。相反，索引两个亚组比例的混合参数P被视为与关键变量值χ相关。从其目标是估计比例的意义上说，新方法类似于逻辑回归。但是，就响应变量所获得的连续值谱而言，用于实现其目标的方法与逻辑回归的方法不同。具体来说，组归属不是直接已知的，而是由一个代理连续变量确定的，其值在组之间重叠。文中给出了应用这种新回归形式的模拟数据和自然数据的示例。我们认为，当在生物标志物可替宁对妊娠结局影响的研究中测量的诱发哮喘发作的化学水平χ或出生体重χ决定是否发生发作或负面结果时，条件切换回归是一种特别有价值的研究工具。（摘要截于250字）
