Manuel Suero

A model of the formation of illusory conjunctions in the time domain

The authors present a model to account for the miscombination of features when stimuli are presented using the rapid serial visual presentation (RSVP) technique (illusory conjunctions in the time domain). It explains the distributions of responses through a mixture of trial outcomes. In some trials, attention is successfully focused on the target, whereas in others, the responses are based on partial information. Two experiments are presented that manipulated the mean processing time of the target-defining dimension and of the to-be-reported dimension, respectively. As predicted, the average origin of the responses is delayed when lengthening the target-defining dimension, whereas it is earlier when lengthening the to-be-reported dimension; in the first case the number of correct responses is dramatically reduced, whereas in the second it does not change. The results, a review of other research, and simulations carried out with a formal version of the model are all in close accordance with the predictions.

Optimization of sample size in controlled experiments: The CLAST rule

Sequential rules are explored in the context of null hypothesis significance testing. Several studies have demonstrated that the fixed-sample stopping rule, in which the sample size used by researchers is determined in advance, is less practical and less efficient than sequential stopping rules. It is proposed that a sequential stopping rule called CLAST (composite limited adaptive sequential test) is a superior variant of COAST (composite open adaptive sequential test), a sequential rule proposed by Frick (1998). Simulation studies are conducted to test the efficiency of the proposed rule in terms of sample size and power. Two statistical tests are used: the one-tailed t test of mean differences with two matched samples, and the chi-square independence test for twofold contingency tables. The results show that the CLAST rule is more efficient than the COAST rule and reflects more realistically the practice of experimental psychology researchers.

Illusory Conjunctions in the Time Domain and the Resulting Time-Course of the Attentional Blink.

Illusory conjunctions in the time domain are errors made in binding stimulus features presented In the same spatial position in Rapid Serial Visual Presentation (RSVP) conditions. Botella, Barriopedro, and Suero (2001) devised a model to explain how the distribution of responses originating from stimuli around the target in the series is generated. They proposed two routes consisting of two sequential attempts to make a response. The second attempt (sophisticated guessing) is only employed if the first one (focal attention) fails in producing an integrated perception. This general outline enables specific predictions to be made and tested related to the efficiency of focal attention in generating responses in the first attempt. Participants had to report the single letter in an RSVP stream of letters that was presented in a previously specified color (first target, T1) and then report whether an X (second target, T2) was or was not presented. Performance on T2 showed the typical U-shaped function across the T1-T2 lag that reflects the attentional blink phenomenon. However, as was predicted by Botella, Barriopedro, and Sueros model, the time-course of the interference was shorter for trials with a correct response to T1 than for trials with a T1 error. Furthermore, longer time-courses of interference associated with pre-target and post-target errors to the first target were indistinguishable.

The Debate on the Ego-Depletion Effect: Evidence from Meta-Analysis with the p-Uniform Method

This research was supported by grant PSI2013-45513-P (Ministerio de Economia y Competitividad, Spain)

Multinomial tree models for assessing the status of the reference in studies of the accuracy of tools for binary classification

Studies that evaluate the accuracy of binary classification tools are needed. Such studies provide 2 × 2 cross-classifications of test outcomes and the categories according to an unquestionable reference (or gold standard). However, sometimes a suboptimal reliability reference is employed. Several methods have been proposed to deal with studies where the observations are cross-classified with an imperfect reference. These methods require that the status of the reference, as a gold standard or as an imperfect reference, is known. In this paper a procedure for determining whether it is appropriate to maintain the assumption that the reference is a gold standard or an imperfect reference, is proposed. This procedure fits two nested multinomial tree models, and assesses and compares their absolute and incremental fit. Its implementation requires the availability of the results of several independent studies. These should be carried out using similar designs to provide frequencies of cross-classification between a test and the reference under investigation. The procedure is applied in two examples with real data.

Parallel processing of stimulus features during RSVP : evidence from the second response

When observers are asked to report a feature of a single target displayed in rapid serial visual presentation, they frequently make errors. Most frequently, a feature from the to-be-reported dimension pertaining to a stimulus presented near the target is reported. These migrations are so-calledillusory conjunctions in the time domain. From parallel models, it is proposed that during the presentation of the series, the response features of the stimuli are extracted. If a high rate of presentation does not enable proper binding processes, the system could base its response on sophisticated guessing on the basis of the relative levels of activation of the available response features. However, the multiple extractions assumption has not received direct empirical support. We report two experiments in which the observers had to report their first and second response candidates. This double response paradigm makes it possible to test the assumption that more than one response feature is available for making a response. Furthermore, the application of the constant ratio rule (following Botella, Barriopedro, & Suero’s, 2001, model) to the first responses allows predictions for the ratios between choices of the items for the second responses. The correlations between the observed and the predicted response proportions were .887 and .956 in the two experiments. This high predictive capacity indicates, first, that the observers have more than one response available, among which to choose, and second, that the choice among responses is determined largely in the same way for both first and second responses. Nevertheless, the small errors in prediction are further reduced if a proportion of pure guesses is assumed in the second responses. These are probably due to memory losses, misidentifications of the features, and other factors impairing performance in second responses in comparison with first responses.

Consequences of sequential sampling for meta-analysis.

Sequential stopping rules allow hypotheses to be tested using smaller sample sizes than are possible under conventional methods, while controlling the Type I and II error rates. However, the consequences of using such procedures when combining studies in a meta-analysis have rarely been discussed. For a primary study to be included in a meta-analysis, it must provide an estimate of the effect size, and it must be possible to calculate the variance of this estimate, which is used for weighting the study. It is therefore crucial to know whether the use of sequential stopping rules introduces any bias in the estimate of the effect size and/or modifies the variance of the estimate. In the present research, both aspects were studied for the CLAST rule, as applied to testing the difference between two means from paired samples, in a variety of scenarios of sample size and population effect size. The results show that although the bias is small, but still larger than that for the fixed-sample rule, the variance of the estimate is much higher with the CLAST sequential stopping rule. The implications of these results for the incorporation of such studies into meta-analyses are discussed. It is recommended to incorporate such studies into meta-analyses by taking only the information conveyed in the initial sample. The authors of primary studies employing sequential rules should report that information when publishing their results.

Assessing Individual Change Without Knowing the Test Properties: Item Bootstrapping

Assessing significant change (or reliable change) in a person often involve comparing the responses of that person in two administrations of a test or scale. Several procedures have been proposed to determine if a difference between two observed scores is statistically significant or rather is within the range of mere random fluctuations due to measurement error. Application of those procedures involve some knowledge of the test properties. But sometimes those procedures cannot be employed because the properties are unknown or are not trustworthy. In this paper we propose the bootstrap of items procedure to create confidence intervals of the individuals scores without using any known psychometric properties of the test. Six databases containing the responses of several groups to one or more subscales have been analyzed using two methods: bootstrap of items and a classical procedure based on confidence intervals to estimate the true score. The rates of significant change obtained were very similar, suggesting that item bootstrapping is a promising solution when other methods cannot be applied.

On the Reality of Illusory Conjunctions

ABSTRACT The reality of illusory conjunctions in perception has been sometimes questioned, arguing that they can be explained by other mechanisms. Most relevant experiments are based on migrations along the space dimension. But the low rate of illusory conjunctions along space can easily hide them among other types of errors. As migrations over time are a more frequent phenomenon, illusory conjunctions can be disentangled from other errors. We report an experiment in which series of colored letters were presented in several spatial locations, allowing for migrations over both space and time. The distribution of frequencies were fit by several multinomial tree models based on alternative hypothesis about illusory conjunctions and the potential sources of free-floating features. The best-fit model acknowledges that most illusory conjunctions are migrations in the time domain. Migrations in space are probably present, but the rate is very low. Other conjunction errors, as those produced by guessing or miscategorizations of the to-be-reported feature, are also present in the experiment. The main conclusion is that illusory conjunctions do exist.

Meta-analysis of the accuracy of tools used for binary classification when the primary studies employ different references.

The quality of tools used in binary classification is evaluated by studies that assess the accuracy of the classification. The empirical evidence is summarized in 2 × 2 contingency tables. These provide the joint frequencies between the true status of a sample and the classification made by the test. The accuracy of the test is better estimated in a meta-analysis that synthesizes the results of a set of primary studies. The true status is determined by a reference that ideally is a gold standard, which means that it is error free. However, in psychology, it is rare that all the primary studies have employed the same reference, and often they have used an imperfect reference with suboptimal accuracy instead of an actual gold standard. An imperfect reference biases both the estimates of the accuracy of the test and the empirical prevalence of the target status in the primary studies. We discuss several strategies for meta-analysis when different references are employed. Special attention is paid to the simplest case, where the meta-analyst has 1 group of primary studies using a reference that can be considered a gold standard and a 2nd group of primary studies using an imperfect reference. A procedure is recommended in which the frequencies from the primary studies with the imperfect reference are corrected prior to the meta-analysis itself. Then, a hierarchical meta-analytic model is fitted. An example with actual data from SCOFF (Sick-Control-One-Fat-Food; Hill, Reid, Morgan, & Lacey, 2010; Morgan, Reid, & Lacey, 1999) a simple but efficient test for detecting eating disorders, is described.