Older adults tend to have slower response times (RTs) than younger adults on cognitive tasks. This makes the examination of domain-specific deficits in aging difficult, as differences between conditions in raw RTs (RT costs) typically increase with slower average RTs. Here, we examine the mapping between 2 established approaches to dealing with this confound in the literature. The first is to use transformed RT costs, with the z-score and proportional transforms both being commonly used. The second is to use mathematical models of choice RT behavior, such as the drift-diffusion model (Ratcliff, 1978). We simulated data for younger and older adults from the drift-diffusion model under 4 scenarios: (a) a domain specific deficit, (b) general slowing, (c) strategic slowing, and (d) a slowing of nondecision processes. In each scenario we varied the size of the difference between younger and older adults in the model parameters, and examined corresponding effect sizes and Type I error rates in the raw and transformed RT costs. The z-score transformation provided better control of Type I error rates than the raw or proportional costs, though did not fully control for differences in the general slowing and strategic slowing scenarios. We recommend that RT analyses are ideally supplemented by analyses of error rates where possible, as these may help to identify the presence of confounds. To facilitate this, it would be beneficial to include conditions that elicit below ceiling accuracy in tasks.
|Journal||Psychology and Aging|
|Publication status||Published - 8 Oct 2018|
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Funding: This work was supported by the ESRC (ES/K002325/1) and by the Wellcome Trust (104943/Z/14/Z)