title: Limitations of log-rank tests for analysing longevity data in biogerontology.
abstract: Log-rank tests are sometimes used to analyse longevity data when other tests should be preferred. When the experimental design involves more than one factor, some authors perform several log-rank tests with the same data, which increases the risk to wrongly conclude that a difference among groups does exist and does not allow to test interactions. When analysing the effect of a single factor with more than two groups, some authors also perform several tests (e.g. comparing a control group to each of the experimental groups), because post hoc analysis is not available with log-rank tests. These errors prevent to fully appreciate the longevity results of these articles and it would be easy to overcome this problem by using statistical methods devoted to one-way or multi-way designs, such as Cox's models, analysis of variance, and generalised linear models.
authors.affiliation: Centre de Recherche sur la Cognition Animale, UMR CNRS 5169, Université Paul-Sabatier, 31062, Toulouse Cedex 9, France, eric.le-bourg@univ-tlse3.fr.
authors.forename: Eric
authors.initials: E
authors.lastname: Le Bourg
mesh_terms: D000368:Aged; D005260:Female; D005853:Geriatrics; D006801:Humans; D008136:Longevity; D008297:Male