Mixed-effects models are being used ever more frequently in the analysis of experimental data. However, in the lme4 package in R the standards for evaluating significance of fixed effects in these models (i.e., obtaining p-values) are somewhat vague. There are good reasons for this, but as researchers who are using these models are required in many cases to report p-values, some method for evaluating the significance of the model output is needed. This paper reports the results of simulations showing that the two most common methods for evaluating significance, using likelihood ratio tests and applying the z distribution to the Wald t values from the model output (t-as-z), are somewhat anti-conservative, especially for smaller sample sizes. Other methods for evaluating significance, including parametric bootstrapping and the Kenward-Roger and Satterthwaite approximations for degrees of freedom, were also evaluated. The results of these simulations suggest that Type 1 error rates are closest to .05 when models are fitted using REML and p-values are derived using the Kenward-Roger or Satterthwaite approximations, as these approximations both produced acceptable Type 1 error rates even for smaller samples.

No abstract

No abstract

In human vision, acuity and color sensitivity are greatest at the center of fixation and fall off rapidly as visual eccentricity increases. Humans exploit the high resolution of central vision by actively moving their eyes three to four times each second. Here we demonstrate that it is possible to classify the task that a person is engaged in from their eye movements using multivariate pattern classification. The results have important theoretical implications for computational and neural models of eye movement control. They also have important practical implications for using passively recorded eye movements to infer the cognitive state of a viewer, information that can be used as input for intelligent human-computer interfaces and related applications.

We report a replication and extension of Ferreira (2003), in which it was observed that native adult English speakers misinterpret passive sentences that relate implausible but not impossible semantic relationships (e.g., The angler was caught by the fish) significantly more often than they do plausible passives or plausible or implausible active sentences. In the experiment reported here, participants listened to the same plausible and implausible passive and active sentences as in Ferreira (2003), answered comprehension questions, and then orally described line drawings of simple transitive actions. The descriptions were analyzed as a measure of structural priming (Bock, 1986). Question accuracy data replicated Ferreira (2003). Production data yielded an interaction: Passive descriptions were produced more often after plausible passives and implausible actives. We interpret these results as indicative of a language processor that proceeds along differentiated morphosyntactic and semantic routes. The processor may end up adjudicating between conflicting outputs from these routes by settling on a "good enough" representation that is not completely faithful to the input.