Table 4. Summary of Common Pitfalls Identified in the Literature Review.

Step	Pitfalls
Aims	Not reporting specific aims
Data-generating mechanism	Not summarizing simulation conditions and data-generating mechanism in a structured way (e.g., bullet points, tables)
	Not providing justification and Monte Carlo uncertainty coupled with a small number of simulation repetitions
Estimands and other targets	Not defining estimands / targets clearly, especially in models with many parameters
Methods	Not clearly listing all of the compared methods and their specifications
Performance measures	Not clearly defining performance measures
	Not clearly defining how performance measures are aggregated
	Not reporting Monte Carlo uncertainty
	Not reporting convergence
Computational aspects	Not reporting computational environment (operating system, software, and package versions)
	Not using persistent repositories for sharing code and data (e.g., publisher or university repositories)
	Not sharing code and data

Note. Pitfalls were not all coded explicitly, but summarized from the quantitative results of the literature review and discussions between the reviewing authors.