1998
DOI: 10.2307/2411330
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Logistic Regression for Empirical Studies of Multivariate Selection

Abstract: Understanding the mechanics of adaptive evolution requires not only knowing the quantitative genetic bases of the traits of interest but also obtaining accurate measures of the strengths and modes of selection acting on these traits. Most recent empirical studies of multivariate selection have employed multiple linear regression to obtain estimates of the strength of selection. We reconsider the motivation for this approach, paying special attention to the effects of nonnormal traits and fitness measures. We a… Show more

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Cited by 267 publications
(299 citation statements)
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“…Many studies of selection use viability as their measure of fitness, so it is possible that any conclusions regarding power derived from the methods presented above might not be applicable to binomially distributed fitnesses (Janzen and Stern 1998). To test for this possibility, for a given theoretical correlation coefficient and sample size, sample datasets were generated under the assumption that the traits were normally distributed ( ϭ 0, 2 ϭ 1) but that fitness was binomially distributed (the probability of being alive, p ϭ 0.1, 0.5, and 0.9; BIVAR, ver.…”
Section: Methodsmentioning
confidence: 99%
“…Many studies of selection use viability as their measure of fitness, so it is possible that any conclusions regarding power derived from the methods presented above might not be applicable to binomially distributed fitnesses (Janzen and Stern 1998). To test for this possibility, for a given theoretical correlation coefficient and sample size, sample datasets were generated under the assumption that the traits were normally distributed ( ϭ 0, 2 ϭ 1) but that fitness was binomially distributed (the probability of being alive, p ϭ 0.1, 0.5, and 0.9; BIVAR, ver.…”
Section: Methodsmentioning
confidence: 99%
“…As values for survival are binary, we used logistic regressions to estimate selection gradients (Schluter, 1988;Janzen & Stern, 1998). All the morphological traits were standardized to have a mean of zero and a standard deviation of 1 (Lande & Arnold, 1983;Janzen & Stern, 1998).…”
Section: Viability Selection In the Wildmentioning
confidence: 99%
“…Consequently, we transformed the logistic regression coefficients and obtained b avggrad , which is comparable to the linear selection gradient (b) obtained through multiple regressions (Janzen & Stern, 1998). Nonlinear selection gradients (c), which describe nonlinear selection on a trait, were calculated by adding the cross-product and squared standardized traits to the logistic regression.…”
Section: Researchmentioning
confidence: 99%
“…All analyses were conducted by using both linear and logistic regression, and the robustness of the results to method of analysis was evaluated. We note that our primary goal was parameter estimation rather than significance testing of individual differentials such that selection estimates from linear regression are likely appropriate (26,37). Whether selection differed significantly among treatments for individual traits was evaluated by using data from all treatments and then testing the significance of interaction between trait value (continuous covariate) and treatment (categorical covariate) in a selection analysis with survival as the dependent variable.…”
Section: )mentioning
confidence: 99%