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Below‐threshold mortality: implications for studies in evolution, ecology and demography
Author(s) -
Promislow,
Tatar,
Pletcher,
Carey
Publication year - 1999
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1046/j.1420-9101.1999.00037.x
Subject(s) - biology , sampling (signal processing) , sample size determination , range (aeronautics) , statistics , ecology , sampling error , mortality rate , demography , observational error , mathematics , computer science , materials science , filter (signal processing) , sociology , composite material , computer vision
Evolutionary biologists, ecologists and experimental gerontologists have increasingly used estimates of age‐specific mortality as a critical component in studies of a range of important biological processes. However, the analysis of age‐specific mortality rates is plagued by specific statistical challenges caused by sampling error. Here we discuss the nature of this ‘demographic sampling error’, and the way in which it can bias our estimates of (1) rates of ageing, (2) age at onset of senescence, (3) costs of reproduction and (4) demographic tests of evolutionary models of ageing. We conducted simulations which suggest that using standard statistical techniques, we would need sample sizes on the order of tens of thousands in most experiments to effectively remove any bias due to sampling error. We argue that biologists should use much larger sample sizes than have previously been used. However, we also present simple maximum likelihood models that effectively remove biases due to demographic sampling error even at relatively small sample sizes.