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.
A Computer-Aided SAS Macro for the Evaluation of the Simulation Performances in Missingness Settings
Published: 07 December 2015 by MDPI AG in MOL2NET, International Conference on Multidisciplinary Sciences session Statistics, Artificial Intelligence, Data Science, Complex Networks Analysis
Keywords: simulation; missing data; bias; validation; SAS macro