
Model validation has become a topic of great interest to many fields such as industry, medicine or even to government. Its main challenge is to provide stable and credible tools so that the decision-maker with the information necessary can make high-consequence judgments. This process requires simulation modelling and consequently, some guidelines or evaluation criteria are essential in order to draw meaningful conclusions. A computer-aided SAS® macro is developed using the SAS/IML programming language. Researchers should provide the dataset to be analyzed and the true values to be compared. As a result, the statistical program shows measures (i.e., number of simulations to be performed, bias, accuracy, coverage, etc…) which help investigators to make decisions with a minimal effort of programming. Numerical results of the aforementioned statistical parameters, plots and a report are returned by the statistical tool. Although this macro is focused on the missingness setting, it is applicable to any other discipline. We encourage researchers to use it to make better statistical assessments of the used methods.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
