Reliable hunting bag statistics are a prerequisite for sustainable harvest management based on quantitative modeling. Estimating the total hunting bag for a given game species is faced with a multiplicity of error sources. Of particular concern is the nonresponse error. We consider that the major cause of nonresponse bias is when the reluctance to respond is related to a null harvest, which leads to a potentially important overestimation. For tackling the nonresponse bias issue, we advocate the repeated subsampling of nonrespondents, with a final phase of personal interview by phone, intended to be without nonresponse. When a 100% response rate is actually reached at the last phase, both total and sampling variance can be estimated without bias, whatever the response rates at the previous phases. The actual case of imperfect response at the last phase is studied using Monte Carlo simulations. For imperfect response at the last phase, we show that the estimators we advocate are biased downwards but that these bias remain very moderate if the response rate at the last phase is high enough, depending on the circumstances. Furthermore, we illustrate that increasing the number of phases improves the nonresponse bias attenuation. In case of a hunting bag collecting scheme prone to a high nonresponse rate, for obtaining a very satisfying nonresponse bias attenuation we advocate relying on the multiphase sampling strategy with two- or three-phases, and a response rate in the last phase of at least 90%.

中文翻译：

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减轻狩猎袋调查中的无响应偏差：多阶段采样策略。

可靠的猎物袋统计数据是基于定量建模进行可持续收成管理的前提。估计给定游戏物种的总狩猎包面临着许多错误源。特别令人关注的是无响应错误。我们认为无响应偏见的主要原因是不愿响应与零收获有关，这可能导致潜在的重要高估。为了解决无回应偏差问题，我们主张对无回应者进行重复抽样，最后阶段是通过电话进行个人面试，目的是避免无回应。当在最后一个阶段实际达到100％的响应率时，无论前一阶段的响应率如何，都可以在没有偏差的情况下估算总方差和采样方差。使用蒙特卡洛模拟研究了最后一个阶段的不完全响应的实际情况。对于最后阶段的不完美响应，我们表明，我们主张的估计量向下偏斜，但是如果最后阶段的响应率足够高（取决于具体情况），则这些偏斜将保持非常适度的状态。此外，我们说明了增加相数可改善无响应偏置衰减。如果狩猎袋收集方案倾向于较高的无响应率，则为了获得非常令人满意的无响应偏差衰减，我们主张采用两相或三相多相采样策略，并且至少在最后一个阶段的响应率至少为90％。我们表明，我们提倡的估计量向下偏斜，但是，如果最后一阶段的响应率足够高（取决于具体情况），则这些偏斜将保持非常适度的状态。此外，我们说明了增加相数可改善无响应偏置衰减。如果狩猎袋收集方案倾向于较高的无响应率，则为了获得非常令人满意的无响应偏差衰减，我们主张采用两相或三相多相采样策略，并且至少在最后一个阶段的响应率至少为90％。我们表明，我们提倡的估计量向下偏斜，但是，如果最后一阶段的响应率足够高（取决于具体情况），则这些偏斜将保持非常适度的状态。此外，我们说明了增加相数可改善无响应偏置衰减。如果狩猎袋收集方案倾向于较高的无响应率，则为了获得非常令人满意的无响应偏差衰减，我们主张采用两相或三相多相采样策略，并且至少在最后一个阶段的响应率至少为90％。