Observing documentary reading by verbal protocol

Verifies the applicability to research on indexers' reading strategies of the process observing technique known as Verbal Protocol or Thinking Aloud. This interpretative-qualitative data collecting technique allows the observation of different kinds of process during the progress of different kinds of tasks. Presents a theoretical investigation into reading and into formal methodological procedures to observe reading processes. Describes details of the methodological procedures adopted in five case studies with analysis of samples of data. The project adopted three kinds of parameters for data analysis: theoretical, normative, empirical (derived from observations made in the first case study). The results are compared, and important conclusions regarding documentary reading are drawn.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.