For a given individual, as the degree of delay discounting for an outcome increases the effective value of that outcome decreases when it is delayed. As the GEE and more conventional statistical tests provide the same pattern of result, we suggest researchers use the GEE because it was designed to handle data that has the structure that is typical of discounting data.ĭelay discounting describes the process by which delayed outcomes lose value ( Mazur, 1987 Odum, 2011a).
Across the simulated data sets, the GEE and the conventional statistical tests generally provided similar patterns of results. The data sets were created using a Monte Carlo method based of an existing data set. To determine if GEE provides similar results as conventional statistical tests, were compared the techniques across 2,000 simulated data sets. Generalized estimating equations (GEE) are one type of mixed-effects model that are designed to handle autocorrelated data, such as within-subject repeated-measures data, and are therefore more appropriate for discounting data. As discounting research questions have become more complex by simultaneously focusing on within-subject and between-group differences conventional statistical testing is often not appropriate for the obtained data.
This research has relied heavily on conventional null hypothesis significance testing that is familiar to psychology in general such as t-tests and ANOVAs. Much of discounting research has focused on differences in the degree of discounting across various groups. Discounting is the process by which outcomes lose value.