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Modelling developmental instability in relation to individual fitness: a fully Bayesian latent variable model approach
Author(s) -
Van Dongen S.
Publication year - 2001
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1046/j.1420-9101.2001.00315.x
Subject(s) - fluctuating asymmetry , stability (learning theory) , antisymmetry , unobservable , bayesian probability , asymmetry , latent variable , statistics , variable (mathematics) , econometrics , latent variable model , biology , mathematics , computer science , machine learning , evolutionary biology , mathematical analysis , linguistics , philosophy , physics , quantum mechanics
Since the influential paper by Palmer and Strobeck in 1986, the statistical analysis of fluctuating asymmetry and developmental stability has received much attention. Most studies deal with one of the following four difficulties: (i) correcting for bias in asymmetry estimates due to measurement error; (ii) quantifying sampling error in the estimation of individual developmental stability using individual asymmetry; (iii) the detection of directional asymmetry and antisymmetry; and (iv) combining data from several traits. Yet, few studies have focused on statistical properties of estimating a relationship between individual developmental stability and other factors (e.g. fitness). In this paper I introduce a fully Bayesian model in which the unobservable individual developmental stability is treated as a latent variable. The latter is then related to individual fitness. I show by means of the analysis of simulated data that this approach has several advantages over traditional techniques. First, the method provides unbiased (but slightly less accurate) estimates of slopes between developmental stability and fitness taking all sources of error into account. Secondly, it allows proper investigation of non‐linear associations. Finally, the model allows unbiased estimation of unobserved fitness of individuals that have been measured on left and right side.