Why the study?
Because some methods used to assess a Type D personality effect have been criticized, this study aimed to investigate the tendency of all commonly used methods to produce false positive Type D effects.
Commonly used statistical methods for assessing Type D personality effects produce inflated false positive rates, suggesting previous research findings should be reconsidered.
Some methods risk inflating false positives for Type D effects; challenges prior findings and leaves open optimal analytic approaches.
Type D personality has been associated with various medical and psychosocial outcomes. Type D's underlying personality traits negative affectivity (NA) and social inhibition (SI) are hypothesized to either additively (NA + SI) or synergistically (NA ∗ SI) affect an outcome. As some of the methods used to assess a Type D effect have been criticized in the past, this study aimed to investigate for all commonly used methods their tendency of producing false positive Type D effect. 324,000 datasets were generated using a Monte Carlo Simulation. Each dataset was analyzed using various methods to assess a Type D effect. Each method's performance was assessed in terms of absolute bias and the percentage of false positive findings. An online application was developed where readers can easily experiment with this simulation. Our simulation showed that all commonly used methods risk producing false positive Type D effects. The only method with adequate false positive rates included the continuous NA and SI main effects, as well as their quadratic effects and their interaction. All commonly used methods to assess a Type D personality effect showed inflated false positive rates in realistic simulation scenarios. All earlier research based only on these methods should be reconsidered.
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Paul Lodder (2020) studied this question.
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