Some exact conditional tests of independence forR ×C cross-classification tables

Exact conditional tests of independence in cross-classification tables are formulated based on the ² statistic and statistics with stronger operational interpretations, such as some nominal and ordinal measures of association. Guidelines for the table dimensions and sample sizes for which the tests are economically implemented on a computer are given. Some selected sample sizes and marginal distributions are used in a numerical comparison between the significance levels of the approximate and exact conditional tests based on the ² statistic.The authors are grateful for the suggestions of the referees and for computer funding provided by the Northeast Regional Data Center at the University of Florida.     

Loglinear Rasch model tests

Existing statistical tests for the fit of the Rasch model have been criticized, because they are only sensitive to specific violations of its assumptions. Contingency table methods using loglinear models have been used to test various psychometric models. In this paper, the assumptions of the Rasch model are discussed and the Rasch model is reformulated as a quasi-independence model. The model is a quasi-loglinear model for the incomplete subgroup × score × item 1 × item 2 × ... × itemk contingency table. Using ordinary contingency table methods the Rasch model can be tested generally or against less restrictive quasi-loglinear models to investigate specific violations of its assumptions.     

Testing a unidimensional,qualitative unfolding model for attitudinal or developmental data

Assuming that subject responses rank order stimuli by preference, statistical methods are presented for testing the hypothesis that responses conform to a unidimensional, qualitative unfolding model and to an a priori stimulus ordering. The model postulates that persons and stimulus variables are ordered along a single continuum and that subjects most prefer stimuli nearest their own position. The underlying continuum need not form an interval scale of the stimulus attribute. The general assumptions of the test for the unfolding model make it suitable for the analysis of structure in attitude responses, preference data, and developmental stage data.This research was supported by a grant from the U.S. Public Health Service (Grant No. 1-R01-MH27861-01) to the University of Minnesota. I wish to thank Sanford Weisberg for his helpful suggestions. I also wish to thank Karen Kitchener and Patricia King for letting me use their data.     

Tests of symmetry in three-way contingency tables

Three-dimensional contingency tables are analyzed, with one variable (e.g., sex) as a factor, and with a natural relation between the other variables (e.g. left and right eye vision). Models of special interest, like symmetry and proportional symmetry between the related variables, and homogeneity across the factor levels, are investigated. Maximum likelihood estimators of parameters and partitions of chi-square goodness-of-fit statistics are explicitly presented; the independence of certain models is noted, and an example is discussed.     

Goodness of fit tests for paired comparison models

A goodness of fit test presented by Andersen is shown to be incorrect. The correct test is described and a re-analysis of Andersen's data is provided.     

Measurement issues associated with conditional reasoning tests: An examination of faking

Conditional reasoning (CR) is a new item format that measures personality by indirectly assessing reliance upon the cognitive biases associated with specific traits (James et al., 2005). Previous research suggests that, relative to self-report measures, responses on CR-based measures are more difficult to distort (LeBreton, Barksdale, Robin, & James, 2007). The issue of response distortion in the context of CR-based measures was evaluated in two studies. Study 1 (within-subjects) and Study 2 (between-subjects) both investigated whether responses on a CR-based test of addiction could be faked when indirect assessment was upheld. Results of both studies indicated that, unlike a self-report measure of a similar construct, the CR-based measure was unaffected by response distortion.     

Exploratory analysis of contingency tables by loglinear formulation and generalizations of correspondence analysis

Goodman's (1979, 1981, 1985) loglinear formulation for bi-way contingency tables is extended to tables with or without missing cells and is used for exploratory purposes. A similar formulation is done for three-way tables and generalizations of correspondence analysis are deduced. A generalized version of Goodman's algorithm, based on Newton's elementary unidimensional method is used to estimate the scores in all cases.This research was partially supported by National Science and Engineering Research Council of Canada, Grant No. A8724. The author is grateful to the reviewers and the editor for helpful comments.     

Many tests of significance: new methods for controlling type I errors

There have been many discussions of how Type I errors should be controlled when many hypotheses are tested (e.g., all possible comparisons of means, correlations, proportions, the coefficients in hierarchical models, etc.). By and large, researchers have adopted familywise (FWER) control, though this practice certainly is not universal. Familywise control is intended to deal with the multiplicity issue of computing many tests of significance, yet such control is conservative--that is, less powerful--compared to per test/hypothesis control. The purpose of our article is to introduce the readership, particularly those readers familiar with issues related to controlling Type I errors when many tests of significance are computed, to newer methods that provide protection from the effects of multiple testing, yet are more powerful than familywise controlling methods. Specifically, we introduce a number of procedures that control the k-FWER. These methods--say, 2-FWER instead of 1-FWER (i.e., FWER)--are equivalent to specifying that the probability of 2 or more false rejections is controlled at .05, whereas FWER controls the probability of any (i.e., 1 or more) false rejections at .05. 2-FWER implicitly tolerates 1 false rejection and makes no explicit attempt to control the probability of its occurrence, unlike FWER, which tolerates no false rejections at all. More generally, k-FWER tolerates k - 1 false rejections, but controls the probability of k or more false rejections at α =.05. We demonstrate with two published data sets how more hypotheses can be rejected with k-FWER methods compared to FWER control.     

The conditional power of randomization tests for single-case effect sizes in designs with randomized treatment order: A Monte Carlo simulation study

The conditional power (CP) of the randomization test (RT) was investigated in a simulation study in which three different single-case effect size (ES) measures were used as the test statistics: the mean difference (MD), the percentage of nonoverlapping data (PND), and the nonoverlap of all pairs (NAP). Furthermore, we studied the effect of the experimental design on the RT’s CP for three different single-case designs with rapid treatment alternation: the completely randomized design (CRD), the randomized block design (RBD), and the restricted randomized alternation design (RRAD). As a third goal, we evaluated the CP of the RT for three types of simulated data: data generated from a standard normal distribution, data generated from a uniform distribution, and data generated from a first-order autoregressive Gaussian process. The results showed that the MD and NAP perform very similarly in terms of CP, whereas the PND performs substantially worse. Furthermore, the RRAD yielded marginally higher power in the RT, followed by the CRD and then the RBD. Finally, the power of the RT was almost unaffected by the type of the simulated data. On the basis of the results of the simulation study, we recommend at least 20 measurement occasions for single-case designs with a randomized treatment order that are to be evaluated with an RT using a 5% significance level. Furthermore, we do not recommend use of the PND, because of its low power in the RT.     

Accuracy of judging others’ traits and states: Comparing mean levels across tests

Tests of accuracy in interpersonal perception take many forms. Often, such tests use designs and scoring methods that produce overall accuracy levels that cannot be directly compared across tests. Therefore, progress in understanding accuracy levels has been hampered. The present article employed several techniques for achieving score equivalency. Mean accuracy was converted to a common metric, pi [Rosenthal, R., & Rubin, D. B. (1989). Effect size estimation for one-sample multiple-choice-type data: Design, analysis, and meta-analysis. Psychological Bulletin, 106, 332–337] in a database of 109 published results representing tests that varied in terms of scoring method (proportion accuracy versus correlation), content (e.g., personality versus affect), number of response options, item preselection, cue channel (e.g., face versus voice), stimulus duration, and dynamism. Overall, accuracy was midway between guessing level and a perfect score, with accuracy being higher for tests based on preselected than unselected stimuli. When item preselection was held constant, accuracy was equivalent for judging affect and judging personality. However, comparisons must be made with caution due to methodological variations between studies and gaps in the literature.     

Old processes,new perspectives: Familiarity is correlated with (not independent of) recollection and is more (not equally) variable for targets than for lures

According to dual-process models of memory, recognition is subserved by two processes: recollection and familiarity. Many variants of these models assume that recollection and familiarity make stochastically independent contributions to performance in recognition tasks and that the variance of the familiarity signal is equal for targets and for lures. Here, we challenge these ‘common-currency’ assumptions. Using a model-comparison approach, featuring the Continuous Dual Process (CDP; Wixted & Mickes, 2010) model as the protagonist, we show that when these assumptions are relaxed, the model’s fits to individual participants’ data improve. Furthermore, our analyses reveal that across items, recollection and familiarity show a positive correlation. Interestingly, this across-items correlation was dissociated from an across-participants correlation between the sensitivities of these processes. We also find that the familiarity signal is significantly more variable for targets than for lures. One striking theoretical implication of these findings is that familiarity—rather than recollection, as most models assume—may be the main contributor responsible for one of the most influential findings of recognition memory, that of subunit zROC slopes. Additionally, we show that erroneously adopting the common-currency assumptions, introduces severe biases to estimates of recollection and familiarity.     

Post-extinction conditional stimulus valence predicts reinstatement fear: Relevance for long-term outcomes of exposure therapy

Exposure therapy for anxiety disorders is translated from fear conditioning and extinction. While exposure therapy is effective in treating anxiety, fear sometimes returns after exposure. One pathway for return of fear is reinstatement: unsignaled unconditional stimuli following completion of extinction. The present study investigated the extent to which valence of the conditional stimulus (CS+) after extinction predicts return of CS+ fear after reinstatement. Participants (N = 84) engaged in a differential fear conditioning paradigm and were randomised to reinstatement or non-reinstatement. We hypothesised that more negative post-extinction CS+ valence would predict higher CS+ fear after reinstatement relative to non-reinstatement and relative to extinction retest. Results supported the hypotheses and suggest that strategies designed to decrease negative valence of the CS+ may reduce the return of fear via reinstatement following exposure therapy.     

The online processing of only if and even if conditional statements: Implications for mental models

A sentential connective like only if or even if merges two simple propositions into a complex statement. This study used a visual world paradigm experiment to explore how this merging process proceeds online. We first presented participants with a short animation, illustrating different simple propositions that are possible to be merged by the sentential connectives. We then auditorily played an only if or an even if statement and recorded participants' eye movements on the concurrent test image. We observed that hearing the sentential connective results in more fixations on the tokens of the appropriate propositions that are eligible to be merged by the sentential connective. Each sentential connective elicited anticipatory effect suggests that once they heard the sentential connective, participants knew which propositions could be merged. We then discussed the implications of our results to the mental model theory of conditionals and the experimental studies reported in literature.     

Hemispheric specialization and independence for word recognition: a comparison of three computational models

Two findings serve as the hallmark for hemispheric specialization during lateralized lexical decision. First is an overall word advantage, with words being recognized more quickly and accurately than non-words (the effect being stronger in response latency). Second, a right visual field advantage is observed for words, with little or no hemispheric differences in the ability to identify non-words. Several theories have been proposed to account for this difference in word and non-word recognition, some by suggesting dual routes of lexical access and others by incorporating separate, and potentially independent, word and non-word detection mechanisms. We compare three previously proposed cognitive theories of hemispheric interactions (callosal relay, direct access, and cooperative hemispheres) through neural network modeling, with each network incorporating different means of interhemispheric communication. When parameters were varied to simulate left hemisphere specialization for lexical decision, only the cooperative hemispheres model showed both a consistent left hemisphere advantage for word recognition but not non-word recognition, as well as an overall word advantage. These results support the theory that neural representations of words are more strongly established in the left hemisphere through prior learning, despite open communication between the hemispheres during both learning and recall.     

Maximum likelihood estimation of the joint covariance matrix for sections of tests given to distinct samples with application to test equating

Consider an old testX consisting ofs sections and two new testsY andZ similar toX consisting ofp andq sections respectively. All subjects are given testX plus two variable sections from either testY orZ. Different pairings of variable sections are given to each subsample of subjects. We present a method of estimating the covariance matrix of the combined test (X ₁, ...,X _s ,Y ₁, ...,Y _p ,Z ₁, ...,Z _q ) and describe an application of these estimation techniques to linear, observed-score, test equating.The author is indebted to Paul W. Holland and Donald B. Rubin for their encouragement and many helpful comments and suggestions that contributed significantly to the development of this paper.This research was supported by the Program Statistics Research Project of the ETS Research Statistics Group.     

The potential of gamification for user education in partial and conditional driving automation: A driving simulator study

Drivers must establish adequate mental models to ensure safe driver-vehicle interaction in combined partial and conditional driving automation. To achieve this, user education is considered crucial. Since gamification has previously shown positive effects on learning motivation and performance, it could serve as a measure to enhance user education on automated vehicles. We developed a tablet-based instruction involving gamified elements and compared it to instruction without gamification and a control group receiving a user manual. After instruction, participants (N = 57) experienced a 30-minute automated drive on a motorway in a fixed-base driving simulator. Participants who received the gamified instruction reported a higher level of intrinsic motivation to learn the provided content. The results also indicate that gamification promotes mental model formation and trust during the automated drive. Taken together, including gamification in user education for automated driving is a promising approach to enhance safe driver-vehicle interaction.     

Robust affective priming effects in a conditional pronunciation task: Evidence for the semantic representation of evaluative information

Based on the hypothesis that information about the valence of words is encoded in a semantic system, we predicted that the match between the valence of a prime and the valence of a target word will influence the pronunciation of the target only if and to the extent that pronunciation is semantically mediated. In line with this prediction, we found affective priming effects (faster pronunciation when prime and target had the same valence than when they had a different valence) only when participants were instructed to read words but not nonwords (Experiment 1) or words that were not names of occupations (Experiment 2). Priming was not significant when participants were asked to read white but not red words (Experiment 1) or words that did not have a frame around them (Experiment 2).     

The computerized scoring algorithm for the autobiographical memory test: updates and extensions for analyzing memories of English-speaking adults

ABSTRACT

The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In the AMT, participants are asked to generate specific memories in response to emotional cue words, and their responses are scored by human experts. Because the manual coding takes some time, particularly when analysing a large dataset, recent studies have proposed computerised scoring algorithms. These algorithms have been shown to reliably discriminate between specific and non-specific memories of English-speaking children and Dutch- and Japanese-speaking adults. The key limitation is that the algorithm is not developed for English-speaking adult memories, which may cover a wider range of vocabulary that the existing algorithm for English-speaking child memories cannot process correctly. In the present study, we trained a new support vector machine to score memories of English-speaking adults. In a performance test (predicting memory specificity against human expert coding), the adult-memory algorithm outperformed the child-memory variant. In another independent performance test, the adult-memory algorithm showed robust performances to score memories that were generated in response to a different set of cues. These results suggest that the adult-memory algorithm reliably scores memory specificity.     

The extended cognition thesis: Its significance for the philosophy of (cognitive) science

While the extended cognition (EC) thesis has gained more followers in cognitive science and in the philosophy of mind and knowledge, our main goal is to discuss a different area of significance of the EC thesis: its relation to philosophy of science. In this introduction, we outline two major areas: (I) The role of the thesis for issues in the philosophy of cognitive science, such as: How do notions of EC figure in theories or research programs in cognitive science? Which versions of the EC thesis appear, and with which arguments to support them? (II) The potentials and limits of the EC thesis for topics in general philosophy of science, such as: Can naturalism perhaps be further advanced by means of the more recent EC thesis? Can we understand “big science” or laboratory research better by invoking some version of EC? And can the EC thesis help in overcoming the notorious cognitive/social divide in science studies?     

Constraining bridges between levels of analysis: A computational justification for locally Bayesian learning

Different levels of analysis provide different insights into behavior: computational-level analyses determine the problem an organism must solve and algorithmic-level analyses determine the mechanisms that drive behavior. However, many attempts to model behavior are pitched at a single level of analysis. Research into human and animal learning provides a prime example, with some researchers using computational-level models to understand the sensitivity organisms display to environmental statistics but other researchers using algorithmic-level models to understand organisms’ trial order effects, including effects of primacy and recency. Recently, attempts have been made to bridge these two levels of analysis. Locally Bayesian Learning (LBL) creates a bridge by taking a view inspired by evolutionary psychology: Our minds are composed of modules that are each individually Bayesian but communicate with restricted messages. A different inspiration comes from computer science and statistics: Our brains are implementing the algorithms developed for approximating complex probability distributions. We show that these different inspirations for how to bridge levels of analysis are not necessarily in conflict by developing a computational justification for LBL. We demonstrate that a scheme that maximizes computational fidelity while using a restricted factorized representation produces the trial order effects that motivated the development of LBL. This scheme uses the same modular motivation as LBL, passing messages about the attended cues between modules, but does not use the rapid shifts of attention considered key for the LBL approximation. This work illustrates a new way of tying together psychological and computational constraints.