{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["76(7)"],"submitter":["Morrissey MB"],"funding":["Royal Society"],"pubmed_abstract":["Log-linear models are widely used for assessing determinants of fitness in empirical studies, for example, in determining how reproductive output depends on trait values or environmental conditions. Similarly, theoretical works of fitness and natural selection employ log-linear models, often with a negative quadratic term, generating Gaussian fitness functions. However, in the specific application of regression-based analysis of natural selection, such models are rarely employed. Rather, OLS regression is the predominant means of assessing the form of natural selection. OLS regressions allow specific evolutionary quantitative parameters, selection gradients, to be estimated, and benefit from the fact that the associated statistical models are easily applied. We examine whether selection gr"],"journal":["Evolution; international journal of organic evolution"],"pagination":["1378-1390"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9546161"],"repository":["biostudies-literature"],"pubmed_title":["Analytical results for directional and quadratic selection gradients for log-linear models of fitness functions."],"pmcid":["PMC9546161"],"pubmed_authors":["Morrissey MB","Goudie IBJ"],"additional_accession":[]},"is_claimable":false,"name":"Analytical results for directional and quadratic selection gradients for log-linear models of fitness functions.","description":"Log-linear models are widely used for assessing determinants of fitness in empirical studies, for example, in determining how reproductive output depends on trait values or environmental conditions. Similarly, theoretical works of fitness and natural selection employ log-linear models, often with a negative quadratic term, generating Gaussian fitness functions. However, in the specific application of regression-based analysis of natural selection, such models are rarely employed. Rather, OLS regression is the predominant means of assessing the form of natural selection. OLS regressions allow specific evolutionary quantitative parameters, selection gradients, to be estimated, and benefit from the fact that the associated statistical models are easily applied. We examine whether selection gr","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Jul","modification":"2025-04-05T20:11:12.332Z","creation":"2025-04-05T20:11:12.332Z"},"accession":"S-EPMC9546161","cross_references":{"pubmed":["35340021"],"doi":["10.1111/evo.14486"]}}