A linear mixed model analysis of masked repetition priming

We examined individual differences in masked repetition priming by re-analysing item-level response-time (RT) data from three experiments. Using a linear mixed model (LMM) with subjects and items specified as crossed random factors, the originally reported priming and word-frequency effects were recovered. In the same LMM, we estimated parameters describing the distributions of these effects across subjects. Subjects' frequency and priming effects correlated positively with each other and negatively with mean RT. These correlation estimates, however, emerged only with a reciprocal transformation of RT (i.e., − 1/RT), justified on the basis of distributional analyses. Different correlations, some with opposite sign, were obtained (1) for untransformed or logarithmic RTs or (2) when correlations were computed using within-subject analyses. We discuss the relevance of the new results for accounts of masked priming, implications of applying RT transformations, and the use of LMMs as a tool for the joint analysis of experimental effects and associated individual differences.