Pseudocontingencies derived from categorically organized memory representations

Pseudocontingencies (PCs) allow for inferences about the contingency between two variables X and Y when the conditions for genuine contingency assessment are not met. Even when joint observations X _i and Y _i about the same reference objects i are not available or are detached in time or space, the correlation r(X _i ,Y _i ) is readily inferred from base rates. Inferred correlations are positive (negative) if X and Y base rates are skewed in the same (different) directions. Such PC inferences afford useful proxies for actually existing contingencies. While previous studies have focused on PCs due to environmental base rates, the present research highlights memory organization as a natural source of PC effects. When information about two attributes X and Y is represented in a hierarchically organized categorical memory code, as category-wise base rates p(X) and p(Y), the reconstruction of item-level information from category base rates will naturally produce PC effects. Three experiments support this contention. When the yes base rates of two respondents in four questionnaire subscales (categories) were correlated, recalled and predicted item-level responses were correlated in the same direction, even when the original responses to specific items within categories were correlated in the opposite direction.     

The nontruncated marginal of a truncated bivariate normal distribution

Inference is considered for the marginal distribution ofX, when (X, Y) has a truncated bivariate normal distribution. TheY variable is truncated, but only theX values are observed. The relationship of this distribution to Azzalini's skew-normal distribution is obtained. Method of moments and maximum likelihood estimation are compared for the three-parameter Azzalini distribution. Samples that are uniformative about the skewness of this distribution may occur, even for largen. Profile likelihood methods are employed to describe the uncertainty involved in parameter estimation. A sample of 87 Otis test scores is shown to be well-described by this model.     

Limited‐information goodness‐of‐fit testing of item response theory models for sparse 2P tables

Bartholomew and Leung proposed a limited‐information goodness‐of‐fit test statistic (Y) for models fitted to sparse 2^P contingency tables. The null distribution of Y was approximated using a chi‐squared distribution by matching moments. The moments were derived under the assumption that the model parameters were known in advance and it was conjectured that the approximation would also be appropriate when the parameters were to be estimated. Using maximum likelihood estimation of the two‐parameter logistic item response theory model, we show that the effect of parameter estimation on the distribution of Y is too large to be ignored. Consequently, we derive the asymptotic moments of Y for maximum likelihood estimation. We show using a simulation study that when the null distribution of Y is approximated using moments that take into account the effect of estimation, Y becomes a very useful statistic to assess the overall goodness of fit of models fitted to sparse 2^P tables.     

Defining reward value by cross-modal scaling

Researchers in comparative psychology often use different food rewards in their studies, with food values defined by a pre-experimental preference test. While this technique rank orders food values, it provides limited information about value differences because preferences may reflect not only value differences, but also the degree to which one good may “substitute” for another (e.g., one food may substitute well for another food, but neither substitutes well for water). We propose scaling the value of food pairs by a third food that is less substitutable for either food offered in preference tests (cross-modal scaling). Here, Cebus monkeys chose between four pairwise alternatives: fruits A versus B; cereal amount X versus fruit A and cereal amount Y versus fruit B where X and Y were adjusted to produce indifference between each cereal amount and each fruit; and cereal amounts X versus Y. When choice was between perfect substitutes (different cereal amounts), preferences were nearly absolute; so too when choice was between close substitutes (fruits); however, when choice was between fruits and cereal amounts, preferences were more modest and less likely due to substitutability. These results suggest that scaling between-good value differences in terms of a third, less-substitutable good may be better than simple preference tests in defining between-good value differences.     

Do people reason rationally about causally related events? Markov violations,weak inferences,and failures of explaining away

Making judgments by relying on beliefs about the causal relationships between events is a fundamental capacity of everyday cognition. In the last decade, Causal Bayesian Networks have been proposed as a framework for modeling causal reasoning. Two experiments were conducted to provide comprehensive data sets with which to evaluate a variety of different types of judgments in comparison to the standard Bayesian networks calculations. Participants were introduced to a fictional system of three events and observed a set of learning trials that instantiated the multivariate distribution relating the three variables. We tested inferences on chains X₁ → Y → X₂, common cause structures X₁ ← Y → X₂, and common effect structures X₁ → Y ← X₂, on binary and numerical variables, and with high and intermediate causal strengths. We tested transitive inferences, inferences when one variable is irrelevant because it is blocked by an intervening variable (Markov Assumption), inferences from two variables to a middle variable, and inferences about the presence of one cause when the alternative cause was known to have occurred (the normative “explaining away” pattern). Compared to the normative account, in general, when the judgments should change, they change in the normative direction. However, we also discuss a few persistent violations of the standard normative model. In addition, we evaluate the relative success of 12 theoretical explanations for these deviations.     

The effects of response-reinforcer contingency on time allocation in the open field

The present experiment explores the effects of the response (1-sec occupancy of a target area in an open field)—reinforcer (intracranial stimulation) contingency on time allocation in the open field in rats. The probability of reinforcement given a response (X) and the probability of reinforcement given the absence of a response (Y) were varied randomly across sessions within a subject. The following (X, Y) values were utilized: (.05, 0), (.15, 0), (.25, 0), (.15, .05), and (.15, .15). The results of this experiment indicate that rate of acquisition of time allocation preference is uniformly rapid during all contingency treatments wherein Y = 0 and is negatively related to the value of Y when X = .15. The relationship between the asymptote of the time allocation acquisition function and the value of X (when Y = 0) is positively sloped and negatively accelerated, while the relationship between asymptote and the value of Y (when X = .15) is negatively sloped with zero acceleration. Proposed contingency metrics are evaluated.     

The conjunction fallacy: a misunderstanding about conjunction?

It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X-and-Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners’ interpretation of the expressions “probability” and “and.” We report two experiments designed to clarify the normative status of typical responses to conjunction problems.     

Verification of algebra step problems: A chronometric study of human problem solving

A class of simple problem solving tasks requiring fast accurate solutions is introduced. In an experiment subjects memorized a mapping rule represented by lists of words labeled by cue words and made true/false decisions about conjunctions of propositions of the form “Y is in the list labeled by X”, written “X → Y”. Response times are analyzed using a “stage modeling” technique where problem solving algorithms are composed using a small set of psychological operations that have real time characteristics specified parametrically. The theoretical analysis shows that response time performance is adequately described in terms of the sequential application of elementary psychological operations. Unexpectedly, it was found that the proposition “X → YandX → Z” was verified as quickly as the apparently simpler “X → Y”. A case is presented for the modeling technique as applied to memory and problem solving tasks in terms of theoretical parsimony, statistical simplicity, and flexibility in investigative empirical research. Suggestions are made as to possible theoretical relations among fast problem solving, more complex and slower problem solving, and research in fundamental memory processes.     

Intuitive prediction: ecological validity versus representativeness

Insufficiently regressive intuitive predictions have been attributed to mistaken reliance on the representativeness heuristic. In contrast, we suggest that intuitive predictions stem from a conceptualization of ‘goodness of prediction’ that differs from the accepted statistical definition in terms of error minimization, namely, ecological validity—that is, representation of the substantive characteristics of the predicted variable Y and its distribution as well as of the relationship between Y and the predictor X—rather than minimization of prediction errors. Simultaneous satisfaction of the above representation requirements is achieved by multivalued prediction: The prediction of different Y′ values for the same X value, resulting in conditional distributions Y′|X for at least some X values. Empirical results supporting this hypothesis are presented and discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

Exact probabilities for contingency tables using binomial coefficients

The use of binomial coefficients in place of factorials to shorten the calculation of exact probabilities for 2 × 2 and 2 ×r contingency tables is discussed. A useful set of inequalities for estimating the cumulative probabilities in the tail of the distribution from the probability of a single table is given. A table of binomial coefficients with four significant places andn through 60 is provided.     

Bounds on variances of estimators for multinomial processing tree models

When there are order constraints among the parameters of a binary, multinomial processing tree (MPT) model, methods have been developed for reparameterizing the constrained MPT into an equivalent unconstrained MPT. This note provides a theorem that is useful in computing bounds on the estimator variances for the parameters of the constrained model in terms of estimator variances of the parameters of the unconstrained model. In particular, we show that if X and Y are random variables taking values in [0,1], then Var[XY]?2(Var[X]+Var[Y]).     

On the misuse of manifest variables in the detection of measurement bias

Measurement invariance (lack of bias) of a manifest variableY with respect to a latent variableW is defined as invariance of the conditional distribution ofY givenW over selected subpopulations. Invariance is commonly assessed by studying subpopulation differences in the conditional distribution ofY given a manifest variableZ, chosen to substitute forW. A unified treatment of conditions that may allow the detection of measurement bias using statistical procedures involving only observed or manifest variables is presented. Theorems are provided that give conditions for measurement invariance, and for invariance of the conditional distribution ofY givenZ. Additional theorems and examples explore the Bayes sufficiency ofZ, stochastic ordering inW, local independence ofY andZ, exponential families, and the reliability ofZ. It is shown that when Bayes sufficiency ofZ fails, the two forms of invariance will often not be equivalent in practice. Bayes sufficiency holds under Rasch model assumptions, and in long tests under certain conditions. It is concluded that bias detection procedures that rely strictly on observed variables are not in general diagnostic of measurement bias, or the lack of bias.Preparation of this article was supported in part by PSC-CUNY grant #661282 to Roger E. Millsap.     

Dual scaling of comparison and reference stimuli in multi-dimensional psychological space

Dzhafarov and Colonius (Psychol. Bull. Rev. 6 (1999)239; J. Math. Psychol. 45(2001)670) proposed a theory of Fechnerian scaling of the stimulus space based on the psychometric (discrimination probability) function of a human subject in a same-different comparison task. Here, we investigate a related but different paradigm, namely, referent-probe comparison task, in which the pair of stimuli (x and y) under comparison assumes substantively different psychological status, one serving as a referent and the other as a probe. The duality between a pair of psychometric functions, arising from assigning either x or y to be the fixed reference stimulus and the other to be the varying comparison stimulus, and the 1-to-1 mapping between the two stimulus spaces X and Y under either assignment are analyzed. Following Dzhafarov and Colonius, we investigate two properties characteristic of a referent-probe comparison task, namely, (i) Regular cross-minimality—for the pair of stimulus values involved in referent-probe comparison, each minimizes a discrimination probability function where the other is treated as the fixed reference stimulus; (ii) Nonconstant self-similarity—the value of the discrimination probability function at its minima is a nonconstant function of the reference stimulus value. For the particular form of psychometric functions investigated, it is shown that imposing the condition of regular cross-minimality on the pair of psychometric functions forces a consistent (but otherwise still arbitrary) mapping between X and Y, such that it is independent of the assignment of reference/comparison status to x and to y. The resulting psychometric differentials under both assignments are equal, and take an asymmetric, dualistic form reminiscent of the so-called divergence measure that appeared in the context of differential geometry of the probability manifold with dually flat connections (Differential Geometric Methods in Statistics, Lecture Notes in Statistics, Vol. 28, Springer, New York, 1985). The pair of divergence functions on X and on Y, respectively, induce a Riemannian metric in the small, with psychometric order (defined in Dzhafarov & Colonius, 1999) equal to 2. The difference between the Finsler-Riemann geometric approach to the stimulus space (Dzhafarov & Colonius, 1999) and this dually-affine Riemannian geometric approach to the dual scaling of the comparison and the reference stimuli is discussed.     

The ontological distinction between units and entities

The base units of the SI include six units of continuous quantities and the mole, which is defined as proportional to the number of specified elementary entities in a sample. The existence of the mole as a unit has prompted comment in Metrologia that units of all enumerable entities should be defined though not listed as base units. In a similar vein, the BIPM defines numbers of entities as quantities of dimension one, although without admitting these entities as base units. However, there is a basic ontological distinction between continuous quantities and enumerable aggregates. The distinction is the basis of the difference between real and natural numbers. This paper clarifies the nature of the distinction: (i) in terms of a set of measurement axioms stated by H?lder; and (ii) using the formalism known in metrology as quantity calculus. We argue that a clear and unambiguous scientific distinction should be made between measurement and enumeration. We examine confusion in metrological definitions and nomenclature concerning this distinction, and discuss the implications of this distinction for ontology and epistemology in all scientific disciplines.     

Blockage Contraction

Blockage contraction is an operation of belief contraction that acts directly on the outcome set, i.e. the set of logically closed subsets of the original belief set K that are potential contraction outcomes. Blocking is represented by a binary relation on the outcome set. If a potential outcome X blocks another potential outcome Y, and X does not imply the sentence p to be contracted, then Y?≠?K ÷ p. The contraction outcome K ÷ p is equal to the (unique) inclusion-maximal unblocked element of the outcome set that does not imply p. Conditions on the blocking relation are specified that ensure the existence of such a unique inclusion-maximal set for all sentences p. Blockage contraction is axiomatically characterized and its relations to AGM-style operations are investigated. In a finite-based framework, every transitively relational partial meet contraction is also a blockage contraction.     

Significance tests to determine the direction of effects in linear regression models

Previous studies have discussed asymmetric interpretations of the Pearson correlation coefficient and have shown that higher moments can be used to decide on the direction of dependence in the bivariate linear regression setting. The current study extends this approach by illustrating that the third moment of regression residuals may also be used to derive conclusions concerning the direction of effects. Assuming non‐normally distributed variables, it is shown that the distribution of residuals of the correctly specified regression model (e.g., Y is regressed on X) is more symmetric than the distribution of residuals of the competing model (i.e., X is regressed on Y). Based on this result, 4 one‐sample tests are discussed which can be used to decide which variable is more likely to be the response and which one is more likely to be the explanatory variable. A fifth significance test is proposed based on the differences of skewness estimates, which leads to a more direct test of a hypothesis that is compatible with direction of dependence. A Monte Carlo simulation study was performed to examine the behaviour of the procedures under various degrees of associations, sample sizes, and distributional properties of the underlying population. An empirical example is given which illustrates the application of the tests in practice.     

Cross-Cultural Evaluation of the International Affective Picture System on an Indian Sample

The International Affective Picture System (IAPS) is widely used in emotion and attention research. Currently, there is neither a standard database of affective images for use in research with Indian population nor data on the way people from India respond to emotional pictures in terms of different dimensions. In the present study, we investigated whether self-reported Indian ratings are comparable to the original normative ratings (based on a North American sample) to evaluate its usability in Indian research context. The ratings were obtained from a sample of eighty Indian participants (age range?=?18 to 29 years, M _age?=?23.7, SD?=?2.67, 45 % females) on a stratified representative sample of 100 IAPS pictures. Similar to the normative data collected from the North American sample in the original IAPS database, the ratings were collected across three dimensions – valence (how pleasant/attractive or unpleasant/aversive), arousal (how calm or excited was the intensity of activation), and dominance (how controlling). Our results indicate similarities in valence ratings, but differences in arousal and dominance ratings between the Indian and the North American samples. The relationship between arousal and valence showed a similar (but less curved) boomerang shaped distribution seen with the North American sample. Unlike the North American sample, slopes were higher and intercepts were different for the Indian sample. However, the Indian sample also showed positivity offset and negative bias like the North American sample. These affective ratings show a fair amount of similarity but care is needed especially with arousal values in using these pictures for research with Indian population. While there are subtle differences in the relationship between different affective dimensions, there are also major similarities across cultures in affective judgments.     

Exploring Longitudinal Mechanisms of Irritability in Children: Implications for Cognitive-Behavioral Intervention

Severe irritability is a common and clinically important problem longitudinally associated with internalizing and externalizing problems in children. To better understand these mechanisms and to inform treatment research, we tested cognitive-behavioral processes as candidate mediators in the paths from irritability to later problems. Methods: A school sample (N = 238, 48% female, ages 8–10) was assessed at ~6-month intervals in fall (T1) and spring (T2) of third to fourth grade, and again the following fall (T3). Measures assessed irritability (T1/predictor); anger and sadness coping, intolerance of uncertainty, and rumination; (T1–T2/mediators); and anxiety, depressive symptoms, reactive aggression, and oppositionality (T1–T3/outcomes). Focused cross-lagged panel models, controlling for gender and grade, were specified to examine full (X_T1 ➔ M_T2 ➔ Y_T3) and half (X_T1 ➔ M_T2; M_T1 ➔ Y_T2) longitudinal mediation. Across one or more intervals, irritability predicted higher depressive symptoms, anxiety, reactive aggression, oppositionality, intolerance of uncertainty, and poor emotion coping. From T1 irritability to T2/T3 outcomes, mediation was found for poor sadness coping leading to reactive aggression and oppositionality; poor anger coping to anxiety, depressive symptoms, and oppositionality; and intolerance of uncertainty to anxiety. Results offer further evidence for internalizing and externalizing outcomes of youth irritability and new evidence suggesting underlying mechanisms. Irritability may confer risk for externalizing problems via poor sadness/anger coping, and for internalizing problems via poor anger coping and intolerance of uncertainty. Theoretical models and psychosocial treatment should consider addressing regulation of various unpleasant emotions as well as psychological flexibility and tolerating uncertainty.     

The application of the first order system transfer function for fitting the 3-arm radial maze learning curve

A mathematical model is described based on the first order system transfer function in the form Y=B3∗exp(−B2∗(X−1))+B4∗(1−exp(−B2∗(X−1))), where X is the learning session number; Y is the quantity of errors, B2 is the learning rate, B3 is resistance to learning and B4 is ability to learn. The model is tested in a light-dark discrimination learning task in a 3-arm radial maze using Wistar and albino rats. The model provided good fits of experimental data under acquisition and reacquisition, and was able to detect strain differences among Wistar and albino rats. The model was compared to Rescorla-Wagner, and was found to be mutually complementary. Comparisons with Tulving’s logarithmic function and Valentine’s hyperbola and the arc cotangent functions are also provided. Our model is valid for fitting averaged group data, if averaging is applied to a subgroup of subjects possessing individual learning curves of an exponential shape.     

Maximum vs. minimum values: Preferences of speakers and listeners for upper and lower limit estimates

Estimates about uncertain quantities can be expressed in terms of lower limits (more than X, minimum X), or upper limits (less than Y, maximum Y). It has been shown that lower limit statements generally occur much more often than upper limit statements (Halberg & Teigen, 2009). However, in a conversational context, preferences for upper and lower limit statements will be moderated by the concerns of the interlocutors. We report three studies asking speakers and listeners about their preferences for lower and upper limit statements, in the domains of distances, durations, and prices. It appears that travellers prefer information about maximum distances and maximum durations, and buyers (but not sellers) prefer to be told about maximum prices and maximum delivery times. Mistaken maxima are at the same time regarded as more “wrong” than mistaken minima. However, this preference for “worst case” information is not necessarily shared by providers of information (advisors), who are also concerned about being blamed if wrong.