Modeling observed animal performance using the Weibull distribution
Author(s) -
Travis J. Hagey,
Jonathan B. Puthoff,
Kristen E. Crandell,
Kellar Autumn,
Luke J. Harmon
Publication year - 2016
Publication title -
journal of experimental biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.367
H-Index - 185
eISSN - 1477-9145
pISSN - 0022-0949
DOI - 10.1242/jeb.129940
Subject(s) - weibull distribution , generality , statistics , maxima , distribution (mathematics) , statistical power , sample size determination , computer science , mathematics , performance art , mathematical analysis , art , psychology , art history , psychotherapist
To understand how organisms adapt, researchers must link performance and microhabitat. However, measuring performance, especially maximum performance, can sometimes be difficult. Here, we describe an improvement over previous techniques that only consider the largest observed values as maxima. Instead, we model expected performance observations via the Weibull distribution, a statistical approach that reduces the impact of rare observations. After calculating group-level weighted averages and variances by treating individuals separately to reduce pseudoreplication, our approach resulted in high statistical power despite small sample sizes. We fitted lizard adhesive performance and bite force data to the Weibull distribution and found that it closely estimated maximum performance in both cases, illustrating the generality of our approach. Using the Weibull distribution to estimate observed performance greatly improves upon previous techniques by facilitating power analyses and error estimations around robustly estimated maximum values.
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