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重新评估资源选择研究中存在污染对照的病例对照模型。

A re-evaluation of a case-control model with contaminated controls for resource selection studies.

机构信息

Department of Fisheries & Wildlife Sciences, University of Missouri, Columbia, MO, USA.

出版信息

J Anim Ecol. 2013 Nov;82(6):1165-73. doi: 10.1111/1365-2656.12092. Epub 2013 May 23.

Abstract
  1. A common sampling design in resource selection studies involves measuring resource attributes at sample units used by an animal and at sample units considered available for use. Few models can estimate the absolute probability of using a sample unit from such data, but such approaches are generally preferred over statistical methods that estimate a relative probability of use. 2. The case-control model that allows for contaminated controls, proposed by Lancaster & Imbens (1996) and Lele (2009), can estimate the absolute probability of using a sample unit from use-availability data. However, numerous misconceptions have likely prevented the widespread application of this model to resource selection studies. We address common misconceptions regarding the case-control model with contaminated controls and demonstrate its ability to estimate the absolute probability of use, prevalence and parameters associated with categorical covariates from use-availability data. 3. We fit the case-control model with contaminated controls to simulated data with varying prevalence (defined as the average probability of use across all sample units) and sample sizes (n1 = 500 used and na = 500 available samples; n1 = 1000 used and na = 1000 available samples). We then applied this model to estimate the probability Ozark hellbenders (Cryptobranchus alleganiensis bishopi) would use a location within a stream as a function of covariates. 4. The case-control model with contaminated controls provided unbiased estimates of all parameters at N = 2000 sample size simulation scenarios, particularly at low prevalence. However, this model produced increasingly variable maximum likelihood estimates of parameters as prevalence increased, particularly at N = 1000 sample size scenarios. We thus recommend at least 500-1000 used samples when fitting the case-control model with contaminated controls to use-availability data. Our application to hellbender data revealed selection for locations with coarse substrate that are close to potential sources of cover. 5. This study unites a disparate literature, addresses and clarifies many commonly held misconceptions and demonstrates that the case-control model with contaminated controls is a viable alternative for estimating the absolute probability of use from use-availability data.
摘要
  1. 在资源选择研究中,一种常见的抽样设计包括在动物使用的样本单元和被认为可用于使用的样本单元上测量资源属性。很少有模型可以从这些数据中估计使用样本单元的绝对概率,但与估计使用相对概率的统计方法相比,这些方法通常更受青睐。

  2. Lancaster 和 Imbens(1996)以及 Lele(2009)提出的允许污染对照的病例对照模型可以从使用可用性数据中估计使用样本单元的绝对概率。然而,许多误解可能阻止了该模型在资源选择研究中的广泛应用。我们解决了关于带污染对照的病例对照模型的常见误解,并展示了它从使用可用性数据中估计使用的绝对概率、流行率和与分类协变量相关的参数的能力。

  3. 我们使用带污染对照的病例对照模型拟合具有不同流行率(定义为所有样本单元使用的平均概率)和样本大小(n1=500 个使用和 na=500 个可用样本;n1=1000 个使用和 na=1000 个可用样本)的模拟数据。然后,我们应用该模型来估计奥扎克地狱蝾螈(Cryptobranchus alleganiensis bishopi)将某个位置用作溪流的函数的概率。

  4. 在 N=2000 个样本大小模拟场景中,带污染对照的病例对照模型提供了所有参数的无偏估计值,特别是在流行率较低的情况下。然而,随着流行率的增加,该模型对参数的最大似然估计变得越来越不稳定,特别是在 N=1000 个样本大小的情况下。因此,当我们将带污染对照的病例对照模型拟合到使用可用性数据时,我们建议至少使用 500-1000 个使用样本。我们对地狱蝾螈数据的应用揭示了对靠近潜在遮蔽物来源的具有粗基质的位置的选择。

  5. 本研究结合了不同的文献,解决并澄清了许多常见的误解,并表明带污染对照的病例对照模型是从使用可用性数据中估计使用的绝对概率的一种可行替代方法。

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