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Aspects of both growth and selectivity affect growth parameter estimation bias

机译:增长和选择性的方面影响生长参数估计偏差

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Selectivity curves for sampling size-at-age data are somewhat infamous for biasing growth curve parameter estimates. However, aspects of growth itself can also feed into this phenomenon and further increase bias into parameter estimates. We performed a simulation study by producing size-at-age data under a variety of growth curve parameter values and length-based selectivity curve parameter values for two selectivity functions by altering parameters both independently and in conjunction. In tests where parameters were altered one at a time the greatest amount of bias in growth curve parameter estimates came from sampling the data using dome-shaped selectivity. In addition, certain aspects of growth (namely variance in size-at-age) enhanced the biasing effect of both dome-shaped and asymptotic selectivity. When all parameters were altered together the greatest bias occurred in instances where length distributions overlapped to a greater degree and when asymptotic selectivity curves were more mildly sloped. We conclude that bias in growth curve parameter estimates is a result of the statistical weighting of both the probability of being a certain size at a given age and the probability of being captured at that size.
机译:用于采样尺寸达时期数据的选择性曲线对于偏置生长曲线参数估计有点臭名昭着。然而,增长本身的各方面也可以进入这种现象,并进一步将偏差增加到参数估计。我们通过在各种生长曲线参数值下产生尺寸 - 曲线参数值和基于长度的选择性曲线参数值来执行模拟研究,通过独立改变参数和结合使用两个选择性函数。在测试中,一次参数改变参数,生长曲线参数估计中最大的偏差估计来自使用圆顶形选择性对数据进行采样。此外,生长的某些方面(即,尺寸尺寸的方差)增强了圆顶形和渐近选择性的偏置效应。当所有参数都在一起改变了最大的偏差,其中长度分布重叠到更大程度,并且当渐近选择性曲线更温和地倾斜时。我们得出结论,生长曲线参数估计的偏差是在给定年龄的特定尺寸的概率和在该尺寸捕获的概率的统计加权的结果。

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