 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)imagesfigure 1.figure 2.figure 3.figure 4.figure 5.figure 6.figure 7.figure 8.figure 9.figure 10.figure 11.figure 12.figure c-1.figure c-1.figure c-1.figure c-1.figure c-1.figure c-1.figure d-1.figure d-2 . 
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