Abstract
Abstract Mayfield logistic regression is a method for analyzing nest-survival data that extends the traditional Mayfield estimator by incorporating explanatory variables (e.g. habitat structure, seasonal effects, or experimental treatments) in a logistic-regression analysis framework. Although Aebischer (1999) previously showed that logistic regression can be used to fit Mayfield models, few ornithologists have put that finding into practice. My purpose here is to reintroduce this underused method of nest-survival analysis, to compare its performance to that of a dedicated survival-analysis program (MARK), and to provide a practical guide for its use. Like the traditional Mayfield method, Mayfield logistic regression accounts for the num ber of “exposure days” for each nest and allows for uncertain fates (censoring), thus avoiding the bias introduced by typical applications of logistic regression. Mayfield logistic regression should be widely applicable when nests are found at various stages in the nestin...
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
