Showing that the race model inequality is not violated

When participants are asked to respond in the same way to stimuli from different sources (e.g., auditory and visual), responses are often observed to be substantially faster when both stimuli are presented simultaneously (redundancy gain). Different models account for this effect, the two most important being race models and coactivation models. Redundancy gains consistent with the race model have an upper limit, however, which is given by the well-known race model inequality (Miller, 1982). A number of statistical tests have been proposed for testing the race model inequality in single participants and groups of participants. All of these tests use the race model as the null hypothesis, and rejection of the null hypothesis is considered evidence in favor of coactivation. We introduce a statistical test in which the race model prediction is the alternative hypothesis. This test controls the Type I error if a theory predicts that the race model prediction holds in a given experimental condition.     

Testing the race model inequality: An algorithm and computer programs

In divided-attention tasks, responses are faster when two target stimuli are presented, and thus one is redundant, than when only a single target stimulus is presented. Raab (1962) suggested an account of this redundant-targets effect in terms of a race model in which the response to redundant target stimuli is initiated by the faster of two separate target detection processes. Such models make a prediction about the probability distributions of reaction times that is often called the race model inequality, and it is often of interest to test this prediction. In this article, we describe a precise algorithm that can be used to test the race model inequality and present MATLAB routines and a Pascal program that implement this algorithm.     

Testing the race inequality: A simple correction procedure for fast guesses

In speeded response tasks with redundant signals, parallel processing of the redundant signals is generally tested using the so-called race inequality. The race inequality states that the distribution of fast responses for a redundant stimulus never exceeds the summed distributions of fast responses for the single stimuli. It has been pointed out that fast guesses (e.g. anticipatory responses) interfere with this test, and a correction procedure (‘kill-the-twin’ procedure) has been suggested. In this note we formally derive this procedure and extend it to the case in which redundant stimuli are presented with onset asynchrony. We demonstrate how the kill-the-twin procedure is used in a statistical test of the race model prediction.     

The race model inequality: interpreting a geometric measure of the amount of violation

An inequality by J. O. Miller (1982) has become the standard tool to test the race model for redundant signals reaction times (RTs), as an alternative to a neural summation mechanism. It stipulates that the RT distribution function to redundant stimuli is never larger than the sum of the distribution functions for 2 single stimuli. When many different experimental conditions are to be compared, a numerical index of violation is very desirable. Widespread practice is to take a certain area with contours defined by the distribution functions for single and redundant stimuli. Here this area is shown to equal the difference between 2 mean RT values. This result provides an intuitive interpretation of the index and makes it amenable to simple statistical testing. An extension of this approach to 3 redundant signals is presented.     

Applying the permutation test to factorial designs

The permutation test follows directly from the procedure in a comparative experiment, does not depend on a known distribution for error, and is sometimes more sensitive to real effects than are the corresponding parametric tests. Despite its advantages, the permutation test is seldom (if ever) applied to factorial designs because of the computational load that they impose. We propose two methods to limit the computation load. We show, first, that orthogonal contrasts limit the computational load and, second, that when combined with Gill’s (2007) algorithm, the factorial permutation test is both practical and efficient. For within-subjects designs, the factorial permutation test is equivalent to an ANOVA when the latter’s assumptions have been met. For between-subjects designs, the factorial test is conservative. Code to execute the routines described in this article may be downloaded from http://brm.psychonomic-journals.org/content/supplemental.     

The Fisher-Pitman permutation test: an attractive alternative to the F test

The Fisher-Pitman permutation test is shown to possess significant advantages over conventional alternatives when analyzing differences among independent samples with unequal variances.     

A test of the deadline model for speed-accuracy tradeoffs

Two experiments were conducted to evaluate the deadline model for speed-accuracy tradeoffs. According to the deadline model, participants in speeded-response tasks terminate stimulus discrimination as soon as it has run to completion or as soon as a predetermined time deadline has arrived, whichever comes first. Speed is traded for accuracy by varying the time deadlines; short deadlines yield fast but sometimes inaccurate responses, whereas long deadlines allow for slow, accurate responses. A new prediction of this model, based on a comparison of reaction time distributions, was derived and tested in experiments involving the joint manipulation of speed stress and stimulus discriminability. Clear violations of this prediction were observed when participants made relative brightness judgments (Experiment 1) and when they made lexical decisions (Experiment 2), rejecting both the deadline model and the fast-guess model. Several alternative models for speed-accuracy tradeoffs, including random-walk and accumulator models, are compatible with the results.     

A goodness of fit test for the rasch model

The Rasch model is an item analysis model with logistic item characteristic curves of equal slope,i.e. with constant item discriminating powers. The proposed goodness of fit test is based on a comparison between difficulties estimated from different scoregroups and over-all estimates. Based on the within scoregroup estimates and the over-all estimates of item difficulties a conditional likelihood ratio is formed. It is shown that—2 times the logarithm of this ratio isx ²-distributed when the Rasch model is true. The power of the proposed goodness of fit test is discussed for alternative models with logistic item characteristic curves, but unequal discriminating items from a scholastic aptitude test.     

The Fisher-Pitman permutation test when testing for differences in mean and variance

The Fisher-Pitman permutation test can detect any type of difference between two samples: hence, a significant Fisher-Pitman permutation test does not necessarily provide evidence for a difference in means. It is possible, however, to test separately for differences in means and variances. Here, we present a recently proposed two-stage procedure to decide whether there are differences in means or variances that can be applied when samples may come from nonnormal distributions with possibly unequal variances.     

Analysis of trend: a permutation alternative to the F test

When the categories of the independent variable in an analysis of variance are quantitative, it is more informative to evaluate the trends in the treatment means than to simply compare differences among the treatment means. A permutation alternative to the conventional F test is shown to possess significant advantages when analyzing trend among quantitative treatments in a one-way analysis of variance. An example with and without an extreme data point illustrates the effectiveness of the permutation alternative for the analysis of trend when homogeneity of variance is compromised.     

A threat in the computer: the race implicit association test as a stereotype threat experience

Three experiments test whether the threat of appearing racist leads White participants to perform worse on the race Implicit Association Test (IAT) and whether self-affirmation can protect from this threat. Experiments 1 and 2 suggest that White participants show a stereotype threat effect when completing the race IAT, leading to stronger pro-White scores when the test is believed to be diagnostic of racism. This effect increases for domain-identified (highly motivated to control prejudice) participants (Experiment 2). In Experiment 3, self-affirmation inoculates participants against stereotype threat while taking the race IAT. These findings have methodological implications for use of the race IAT and theoretical implications concerning the malleability of automatic prejudice and the potential interpersonal effects of the fear of appearing racist.     

A test of the Dual Filial Piety model

Filial piety is a central concept in Confucianism, containing important ideas about how children should treat their parents. Research over the past two decades has resulted in conflicting findings over whether filial piety is beneficial or harmful to individual development. The Dual Filial Piety model integrates these conflicting findings and suggests neither assessment of filial piety is appropriate. The present study offers empirical evidence in support of the dual model and offers commentary on the role of filial piety in modern Chinese society and directions for future research.     

Social cognitive model of adjustment to engineering majors: Longitudinal test across gender and race/ethnicity

We conducted a longitudinal test of a social cognitive model of academic adjustment in a sample of 732 engineering students. The model, designed to explain students' satisfaction with and intentions to persist in their majors, integrated features of social cognitive career theory's (SCCT) segmental models of satisfaction, interest, choice, and performance (Lent & Brown, 2006; Lent, Brown, & Hackett, 1994). Students completed measures of academic support, self-efficacy, outcome expectations, interests, satisfaction, positive affect, and intended persistence at three time points (at the end of their second, third, and fourth semesters in engineering). A bidirectional version of the model offered good fit to the data, both in the larger sample and across gender and racial/ethnic groups. Self-efficacy was the most reliable direct predictor of academic satisfaction and intended persistence across the third and fourth semesters, though other social cognitive variables also contributed, either directly or indirectly, to predictions at one time point or the other. We consider implications of the findings for further research and practice on academic adjustment and persistence in STEM fields.     

A maximin model for IRT-based test design with practical constraints

A maximin model for IRT-based test design is proposed. In the model only the relative shape of the target test information function is specified. It serves as a constraint subject to which a linear programming algorithm maximizes the information in the test. In the practice of test construction, several demands as linear constraints in the model. A worked example of a text construction problem with practical constraints is presented. The paper concludes with a discussion of some alternative models of test construction.The authors are indebted to Jos J. Adea for suggesting Equation 17 as a Simplification of an earlier version of this constraint. This research was suuorted in part by a grant from the Dutch Organization for Research (NWO) through the Foundation for Psychological and Psychonomic Research in the Netherlands (Psychon).     

A test of the four-factor model of impulsivity-related traits

In a recent article, Whiteside and Lynam [Person. Indiv. Diff. 30 (2001) 669] proposed a new model for understanding personality pathways to impulsive behavior. Their UPPS model maintains that there are four personality dimensions that are related differentially to impulsive behaviors: urgency, sensation seeking, (lack of) premeditation, and (lack of) perseverance. The purpose of the current study was to provide validation for this model and to test some of the specific hypotheses offered by Whiteside and Lynam. The sample used in this study consisted of 481 individuals who completed mailed surveys at age 20 and an in-depth laboratory protocol at age 21. Zero-order correlations and multiple regression analyses were used to examine the relations between the four personality traits and various forms of externalizing behaviors, several types of internalizing psychopathology, and intelligence. Results revealed that the four traits were differentially related to various behaviors and forms of psychopathology consistent with many of Whiteside and Lynam's predictions. Therefore, the UPPS model does appear to offer a novel and useful way of understanding behaviors and forms of psychopathology considered to be characterized by some form of impulsivity.