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领域中选择性报告非显著性结果（selective reporting of non-significance）和/或反向P值操控（reverse P-hacking）的存在性，对相关数据开展了分析。
2018年2月1日，我们在ISI Web of Science数据库中检索了1990年至2018年间发表于3本顶级行为生态学期刊——《动物行为》（Animal Behaviour）、《行为生态学》（Behavioral Ecology）及《行为生态学与社会生物学》（Behavioral Ecology and Sociobiology）——且在“主题”字段包含检索词“experiment* AND control*”的文献，共检索得到1081篇。随后，我们对上述文献展开筛查，以查找其中针对“受试对象被随机分配至各组时，处理组与对照组间混杂变量（confounding variables）的均值是否存在差异”所开展的检验。我们仅纳入基于受试个体或受试群体的测量结果所得到的混杂变量（例如体重、血糖、窝仔数/窝卵数）。为筛选出包含合格数据的文献，我们首先阅读文献的摘要、方法与结果部分，判断是否存在迹象表明该研究可能包含“检验对照组与处理组间混杂变量存在差异”的内容（即涉及实验操控的研究）。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-values）或统计学显著性表述、样本量。