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dc.contributor.authorFay, Rémi
dc.contributor.authorAuthier, Matthieu
dc.contributor.authorHamel, Sandra
dc.contributor.authorJenouvrier, Stéphanie
dc.contributor.authorvan de Pol, 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
dc.contributor.authorLarue, Benjamin
dc.contributor.authorLe Coeur, Christie
dc.contributor.authorGamelon, Marlène
dc.contributor.authorMacdonald, Kaitlin R.
dc.contributor.authorMoiron, Maria
dc.contributor.authorNicol-Harper, 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.accessioned2022-02-05T20:21:54Z
dc.date.available2022-02-05T20:21:54Z
dc.date.issued2021-09-24
dc.description.abstract<ol type="1"> <li>An 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.</li> <li>Using simulations, we estimated the reliability of multivariate mixed effect models for estimating correlated fixed individual heterogeneity in demographic parameters modelled 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.</li> <li>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.</li> <li>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 modelled 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 behavioural and evolutionary studies.</li> </ol>en_US
dc.identifier.citationFay R, Authier, Hamel, Jenouvrier, van de Pol, Cam, Gaillard, Yoccoz, Acker P, Allen, Aubry, Bonenfant, Caswell, Coste CFD, Larue, Le Coeur, Gamelon, Macdonald, Moiron, Nicol-Harper, Pelletier, Rotella, Teplitsky, Touzot, Wells, Sæther. Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables. Methods in Ecology and Evolution. 2021;13(1):91-104en_US
dc.identifier.cristinIDFRIDAID 1964344
dc.identifier.doi10.1111/2041-210X.13728
dc.identifier.issn2041-210X
dc.identifier.urihttps://hdl.handle.net/10037/23927
dc.language.isoengen_US
dc.publisherBritish Ecological Societyen_US
dc.relation.journalMethods in Ecology and Evolution
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.subjectVDP::Mathematics and natural science: 400::Zoology and botany: 480en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480en_US
dc.titleQuantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variablesen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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