Dataset and supplementary information for the article entitled: "Let's DAG in - How DAGs can help Behavioural Ecology be more transparent"

The dataset contains list of articles, whether they contain a DAG or not and the number of variables they used in a single analysis.

To quantify the current use of DAGs in behavioural ecology, we reviewed 245 recent articles from two well-known journals in the field- Behavioral Ecology (Volume 34, Issues 4-6 and Volume 35, Issues 1-3 from July/ August 2023 to May/June 2024) and Animal Behaviour (Issues 210-215, April 2024 to September 2024) for their use of DAGs in their methods and as a justification for their statistical analysis. Out of 245 articles, 7 were papers with theoretical modeling studies and hence were not considered, and one paper did not conduct a statistical analysis. We went through the methods, statistical analyses, results and sometimes even the R code to count the maximum number of variables that were used within a single analysis (‘Max_Nr_Variables_in_Single_Analysis’). We counted all the variables within a single model, which was usually a linear mixed model, and we picked the number of variables in the largest model. For eg, y~z1+z2+(1|a1)+(1|a2) has 5 variables within a single model, including the response variable. This is because, to formulate such a statistical model from a DAG, it would need to contain at least 5 variables or more. Therefore, it is a conservative estimate of the total number of variables that behavioural ecologists measure and add to their statistical models. From our review of the articles, we found that, on average, studies used 6 variables in a single statistical regression model, with a range of 2 – 23 variables (as illustrated in the histogram below)