Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables

dc.contributor.authorFay, Rémi
dc.contributor.authorAuthier, Matthieu
dc.contributor.authorHamel, Sandra
dc.contributor.authorJenouvrier, Stéphanie
dc.contributor.authorPol, Martijn
dc.contributor.authorCam, Emmanuelle
dc.contributor.authorGaillard, Jean‐Michel
dc.contributor.authorYoccoz, Nigel G.
dc.contributor.authorAcker, Paul
dc.contributor.authorAllen, Andrew
dc.contributor.authorAubry, Lise M.
dc.contributor.authorBonenfant, Christophe
dc.contributor.authorCaswell, Hal
dc.contributor.authorCoste, Christophe F. D. Coste
dc.contributor.authorLarue, Benjamin
dc.contributor.authorCoeur, Christie Le
dc.contributor.authorGamelon, Marlène
dc.contributor.authorMacdonald, Kaitlin R.
dc.contributor.authorMoiron, Maria
dc.contributor.authorNicol‐Harpe, Alex
dc.contributor.authorPelletier, Fanie
dc.contributor.authorRotella, Jay J.
dc.contributor.authorTeplitsky, Celine
dc.contributor.authorTouzot, Laura
dc.contributor.authorWells, Caitlin P.
dc.contributor.authorSæther, Bernt‐Erik
dc.date.accessioned2022-09-23T17:25:48Z
dc.date.available2022-09-23T17:25:48Z
dc.date.issued2021-10
dc.descriptionThis is the peer reviewed version of the following article: [Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables. Methods in Ecology and Evolution 13, 1 p91-104 (2021)], which has been published in final form at https://doi.org/10.1111/2041-210X.13728. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html#3.en_US
dc.description.abstractAn increasing number of empirical studies aim to quantify individual variation in demographic parameters because these patterns are key for evolutionary and ecological processes. Advanced approaches to estimate individual heterogeneity are now using a multivariate normal distribution with correlated individual random effects to account for the latent correlations among different demographic parameters occurring within individuals. Despite the frequent use of multivariate mixed models, we lack an assessment of their reliability when applied to Bernoulli variables. Using simulations, we estimated the reliability of multivariate mixed effect models for estimating correlated fixed individual heterogeneity in demographic parameters modeled with a Bernoulli distribution. We evaluated both bias and precision of the estimates across a range of scenarios that investigate the effects of life-history strategy, levels of individual heterogeneity and presence of temporal variation and state dependence. We also compared estimates across different sampling designs to assess the importance of study duration, number of individuals monitored and detection probability. In many simulated scenarios, the estimates for the correlated random effects were biased and imprecise, which highlight the challenge in estimating correlated random effects for Bernoulli variables. The amount of fixed among-individual heterogeneity was frequently overestimated, and the absolute value of the correlation between random effects was almost always underestimated. Simulations also showed contrasting performances of mixed models depending on the scenario considered. Generally, estimation bias decreases and precision increases with slower pace of life, large fixed individual heterogeneity and large sample size. We provide guidelines for the empirical investigation of individual heterogeneity using correlated random effects according to the life-history strategy of the species, as well as, the volume and structure of the data available to the researcher. Caution is warranted when interpreting results regarding correlated individual random effects in demographic parameters modeled with a Bernoulli distribution. Because bias varies with sampling design and life history, comparisons of individual heterogeneity among species is challenging. The issue addressed here is not specific to demography, making this warning relevant for all research areas, including behavioral and evolutionary studies.en_US
dc.identifier.citationFay, Rémi, Matthieu Authier, Sandra Hamel, Stéphanie Jenouvrier, Martijn Van De Pol, Emmanuelle Cam, Jean‐michel Gaillard et al. "Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables." Methods in Ecology and Evolution 13, no. 1 (2022): 91-104.en_US
dc.identifier.issn2041-210X
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/17214
dc.language.isoen_USen_US
dc.publisherWileyen_US
dc.rightscopyright Wiley 2021en_US
dc.rights.urihttps://web.archive.org/web/20200106202133/https://onlinelibrary.wiley.com/library-info/products/price-listsen_US
dc.rights.urihttp://web.archive.org/web/20190530141919/https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.htmlen_US
dc.subjectaccuracyen_US
dc.subjectamong-individual variationen_US
dc.subjectcapture-recaptureen_US
dc.subjectGLMMsen_US
dc.subjectindividual qualityen_US
dc.subjectjoint mixed modelsen_US
dc.subjectmultivariate normal distributionen_US
dc.subjectprecisionen_US
dc.titleQuantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variablesen_US
dc.typeArticleen_US
mus.citation.extentfirstpage1en_US
mus.citation.extentlastpage14en_US
mus.citation.issue1en_US
mus.citation.journaltitleMethods in Ecology and Evolutionen_US
mus.citation.volume13en_US
mus.identifier.doi10.1111/2041-210X.13728en_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentEcology.en_US
mus.relation.universityMontana State University - Bozemanen_US

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