1. O'Hara and Kotze (Methods Ecol Evol 1: 118–122, 2010) present simulation results that appear to show very poor behaviour (as judged by bias and overall accuracy) of linear models applied to count data, especially in relation to GLM analysis.
2. We considered O'Hara and Kotze's (2010) comparisons, and determined that the finding occurred primarily because the quantity that they estimated in their simulations of the linear model analysis (the mean of a transformation of the count data) was not the same quantity that was simulated and to which the results were compared (the logarithm of the mean of the count data). We correct this discrepancy, re‐run O'Hara and Kotze's simulations and add additional simple analyses.
3. We found that the apparent superiority of the GLMs over linear models in O'Hara and Kotze's (2010) simulations was primarily an artefact of divergence in the meanings of results from the two analyses. After converting results from linear model analyses of transformed data to estimators of the same quantity as provided by the GLM, results from both analyses rarely differed substantially. Furthermore, under the circumstances considered by O'Hara and Kotze, we find that an even simpler implementation of linear model analysis, inference of the mean of the raw data, performs even better and gives identical results to the GLM.
4. While the analysis of count data with GLMs can certainly provide many benefits, we strongly caution against interpreting O'Hara and Kotze's (2010) results as evidence that simpler approaches are severely flawed.

中文翻译：

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关于计数数据分析的建议

1. O'Hara和Kotze（Methods Ecol Evol 1：118–122，2010）给出的模拟结果似乎表明，用于计数数据的线性模型的行为（通过偏差和整体准确性判断）非常差，尤其是与GLM分析有关。
2. 我们考虑了O'Hara和Kotze（2010）的比较，并确定该发现主要是因为他们在线性模型分析的模拟中估算的数量（计数数据转换的平均值）与模拟并与结果进行比较（计数数据平均值的对数）。我们纠正了这一差异，重新运行了O'Hara和Kotze的模拟并添加了其他简单分析。
3. 我们发现，在O'Hara和Kotze（2010）的模拟中，GLM相对于线性模型的明显优越性主要是两种分析结果含义存在差异的伪影。将转换后的数据的线性模型分析的结果转换为GLM提供的相同数量的估计量后，这两种分析的结果几乎没有实质性差异。此外，在O'Hara和Kotze所考虑的情况下，我们发现线性模型分析的一种甚至更简单的实现，即对原始数据的均值的推论，效果甚至更好，并且与GLM的结果相同。
4. 虽然使用GLM分析计数数据无疑可以带来很多好处，但我们强烈建议不要将O'Hara和Kotze（2010）的结果解释为简单方法存在严重缺陷的证据。