Arid
DOI10.1016/j.tpb.2012.02.003
Estimating covariation between vital rates: A simulation study of connected vs. separate generalized linear mixed models (GLMMs)
Evans, Margaret E. K.1; Holsinger, Kent E.2
通讯作者Evans, Margaret E. K.
来源期刊THEORETICAL POPULATION BIOLOGY
ISSN0040-5809
出版年2012
卷号82期号:4页码:299-306
英文摘要

Covariation between vital rates is recognized as an important pattern to be accounted for in demographic modeling. We recently introduced a model for estimating vital rates and their covariation as a function of known and unknown effects, using generalized linear mixed models (GLMM’s) implemented in a hierarchical Bayesian framework (Evans et al., 2010) In particular, this model included a model-wide year effect (YEAR) influencing all vital rates, which we used to estimate covariation between vital rates due to exogenous factors not directly included in the model. This YEAR effect connected the GLMMs of vital rates into one large model; we refer to this as the "connected GLMMs" approach. Here we used a simulation study to evaluate the performance of a simplified version of this model, compared to separate GLMMs of vital rates, in terms of their ability to estimate correlations between vital rates. We simulated data from known relationships between vital rates and a covariate, inducing correlations among the vital rates. We then estimated those correlations from the simulated data using connected vs. separate GLMMs with year random effects. We compared precision and accuracy of estimated vital rates and their correlations under three scenarios of the pervasiveness of the exogenous effect (and thus true correlations). The two approaches provide equally good point estimates of vital rate parameters, but connected GLMMs provide better estimates of covariation between vital rates than separate GLMMs, both in terms of accuracy and precision, when the common influence on vital rates is pervasive. We discuss the situations where connected GLMMs might be best used, as well as further areas of investigation for this approach. (C) 2012 Elsevier Inc. All rights reserved.


英文关键词Vital rate covariation Generalized linear mixed models Year effects Hierarchical Bayesian model Demography Transition matrix model
类型Article
语种英语
国家France ; USA
收录类别SCI-E
WOS记录号WOS:000311981400007
WOS关键词POPULATION-GROWTH RATE ; FLORIDA SCRUB MINT ; VARIABLE ENVIRONMENTS ; DESERT ANNUALS ; VIABILITY ; DYNAMICS ; AGE ; DEMOGRAPHY ; FITNESS ; FIRE
WOS类目Ecology ; Evolutionary Biology ; Genetics & Heredity ; Mathematical & Computational Biology
WOS研究方向Environmental Sciences & Ecology ; Evolutionary Biology ; Genetics & Heredity ; Mathematical & Computational Biology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/175176
作者单位1.Museum Natl Hist Nat, Origin Struct & Evolut Biodivers UMR 7205, F-75231 Paris 05, France;
2.Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT 06269 USA
推荐引用方式
GB/T 7714
Evans, Margaret E. K.,Holsinger, Kent E.. Estimating covariation between vital rates: A simulation study of connected vs. separate generalized linear mixed models (GLMMs)[J],2012,82(4):299-306.
APA Evans, Margaret E. K.,&Holsinger, Kent E..(2012).Estimating covariation between vital rates: A simulation study of connected vs. separate generalized linear mixed models (GLMMs).THEORETICAL POPULATION BIOLOGY,82(4),299-306.
MLA Evans, Margaret E. K.,et al."Estimating covariation between vital rates: A simulation study of connected vs. separate generalized linear mixed models (GLMMs)".THEORETICAL POPULATION BIOLOGY 82.4(2012):299-306.
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