Reverse P-hacking: when non-significant results are preferred (dataset)

The data were analysed for the presence of selective reporting of non-significance and/or reverse P-hacking in the field of behavioural ecology.<br>On 1 February 2018, we searched for articles published between 1990 and 2018 in three leading behavioural ecology journals: <i>Animal Behaviour, Behavioral Ecology</i>, and <i>Behavioral Ecology and Sociobiology,</i> that had ‘experiment* AND control*’ in the ‘topic’ category in the ISI Web of Science database (1081 articles). We then searched these articles for tests of whether the mean value of confounding variables differed between treatment(s) and control groups where subjects were randomly assigned to groups. We only included confounding variables that involved measurements made on test subjects or groups of subjects (e.g. body mass, blood glucose, brood size). To identify papers with suitable data, we first read Abstract, Methods and Results to see if there was any indication that the study was likely to include tests for confounding variables differing between control and treatment groups (i.e. studies that involved experimental manipulation). We recorded: the name of the confounding variable, P-values or statistical significance statements associated with tests for a difference, the sample sizes.本研究针对行为生态学（behavioural ecology）领域中，无统计学显著性结果的选择性报告（selective reporting of non-significance）以及反向P值操纵（reverse P-hacking）现象的存在性，对相关数据展开了分析。 2018年2月1日，我们在ISI Web of Science数据库（ISI Web of Science）的“主题”类别中，检索了1990年至2018年间发表于三本顶级行为生态学期刊——《动物行为》（Animal Behaviour）、《行为生态学》（Behavioral Ecology）以及《行为生态学与社会生物学》（Behavioral Ecology and Sociobiology）——且包含检索词‘experiment* AND control*’的文献，最终共获取1081篇文章。 随后，我们对这些文献进行筛查，以查找涉及「处理组（treatment）与随机分配受试对象的对照组（control group）之间，混杂变量（confounding variables）均值是否存在差异」的检验研究。 我们仅纳入针对受试个体或受试群体开展测量所得的混杂变量（例如体质量、血糖、窝卵数）。 为筛选出包含可用数据的文献，我们首先阅读文献的摘要、方法与结果部分，以判断该研究是否存在检验对照组与处理组间混杂变量差异的相关迹象，即涉及实验操纵的研究。 我们记录了以下信息：混杂变量名称、与差异检验相关的P值（P-value）或统计学显著性表述，以及样本量。