Influence of multiple categories on the prediction of unknown properties

Knowing an item's category helps us predict its unknown properties. Previous studies suggest that when asked to evaluate the probability of an unknown property, people tend to consider only an item's most likely category, ignoring alternative categories. In the present study, property prediction took the form of either a probability rating or a speeded binary-choice judgment. In keeping with past findings, the subjects ignored alternative categories in their probability ratings. However, their binary-choice judgments were influenced by alternative categories. This novel finding suggests that the way in which category knowledge is used in prediction depends critically on the form of the prediction.     

Nonconscious influence of masked stimuli on response selection is limited to concrete stimulus-response associations

A pattern-masked arrow negatively biased the "free choice" between 2 manual responses or between 2 vocal responses. This apparently nonconscious influence occurred only when the free-choice trials were intermixed randomly with other trials that terminated in fully visible arrows, which directed a response of the same modality (manual vs. vocal) as that involved in the free-choice test trials. This indicates that recent conscious processing of the association between specific stimuli and specific responses is needed to activate the nonconscious influence of masked arrows on response selection. Because this influence occurred only when a concrete association was activated, it appears not to be based on deep comprehension of the stimuli and instead is attributable to simple stimulus-response bonds.     

Multiple-object tracking is based on scene, not retinal, coordinates

This study tested whether multiple-object tracking-the ability to visually index objects on the basis of their spatiotemporal history-is scene based or image based. Initial experiments showed equivalent tracking accuracy for objects in 2-D and 3-D motion. Subsequent experiments manipulated the speeds of objects independent of the speed of the scene as a whole. Results showed that tracking accuracy was influenced by object speed but not by scene speed. This held true whether the scene underwent translation, zoom, rotation, or even combinations of all 3 motions. A final series of experiments interfered with observers' ability to see a coherent scene by moving objects at different speeds from one another and by distorting the perception of 3-D space. These reductions in scene coherence led to reduced tracking accuracy, confirming that tracking is accomplished using a scene-based, or allocentric, frame of reference.     

How does attention select and track spatially extended objects? New effects of attentional concentration and amplification

Real-world situations involve attending to spatially extended objects, often under conditions of motion and high processing load. The present experiments investigated such processing by requiring observers to attentionally track a number of long, moving lines. Concurrently, observers responded to sporadic probes as a measure of the distribution of attention across the lines. The results revealed that attention is concentrated at the centers of lines during tracking, despite their uniformity, and that this center advantage grew as the lines became longer: Not only did observers get worse near the endpoints, but they became better at the lines' centers, as if attention became more concentrated as the objects became more extended. These results begin to show how attention is flexibly allocated in online visual processing to extended dynamic objects.     

Understanding and using the Implicit Association Test: II. Method variables and construct validity

The Implicit Association Test (IAT) assesses relative strengths of four associations involving two pairs of contrasted concepts (e.g., male-female and family-career). In four studies, analyses of data from 11 Web IATs, averaging 12,000 respondents per data set, supported the following conclusions: (a) sorting IAT trials into subsets does not yield conceptually distinct measures; (b) valid IAT measures can be produced using as few as two items to represent each concept; (c) there are conditions for which the administration order of IAT and self-report measures does not alter psychometric properties of either measure; and (d) a known extraneous effect of IAT task block order was sharply reduced by using extra practice trials. Together, these analyses provide additional construct validation for the IAT and suggest practical guidelines to users of the IAT.     

An abductive theory of scientific method

A broad theory of scientific method is sketched that has particular relevance for the behavioral sciences. This theory of method assembles a complex of specific strategies and methods that are used in the detection of empirical phenomena and the subsequent construction of explanatory theories. A characterization of the nature of phenomena is given, and the process of their detection is briefly described in terms of a multistage model of data analysis. The construction of explanatory theories is shown to involve their generation through abductive, or explanatory, reasoning, their development through analogical modeling, and their fuller appraisal in terms of judgments of the best of competing explanations. The nature and limits of this theory of method are discussed in the light of relevant developments in scientific methodology.     

Using data augmentation to obtain standard errors and conduct hypothesis tests in latent class and latent transition analysis

Latent class analysis (LCA) provides a means of identifying a mixture of subgroups in a population measured by multiple categorical indicators. Latent transition analysis (LTA) is a type of LCA that facilitates addressing research questions concerning stage-sequential change over time in longitudinal data. Both approaches have been used with increasing frequency in the social sciences. The objective of this article is to illustrate data augmentation (DA), a Markov chain Monte Carlo procedure that can be used to obtain parameter estimates and standard errors for LCA and LTA models. By use of DA it is possible to construct hypothesis tests concerning not only standard model parameters but also combinations of parameters, affording tremendous flexibility. DA is demonstrated with an example involving tests of ethnic differences, gender differences, and an Ethnicity x Gender interaction in the development of adolescent problem behavior.     

Teaching research ethics: Can web-based instruction satisfy appropriate pedagogical objectives?

Ethical tasks faced by researchers in science and engineering as they engage in research include recognition of moral problems in their practice, finding solutions to those moral problems, judging moral actions and engaging in preventive ethics. Given these issues, appropriate pedagogical objectives for research ethics education include (1) teaching researchers to recognize moral issues in their research, (2) teaching researchers to solve practical moral problems in their research from the perspective of the moral agent, (3) teaching researchers how to make moral judgments about actions, and (4) learning to engage in preventive ethics. If web-based research ethics education is intended to be adequate and sufficient for research ethics education, then it must meet those objectives. However there are reasons to be skeptical that it can.     

Validity of test score interpretations for three self-concept measures based on differing theoretical models

Three theoretical models have been proposed to represent self-concept: (a) unidimensional; (b) multidimensional; (c) multidimensional hierarchical. Inventories have been developed under each of the three competing theoretical models; which model best represents self-concept is unclear. Typically, self-concept construct validation has utilized various approaches including correlational, multitrait-multimethod, and factor analytic methods. Another method, however, for assessing validity would be to determine the consequences of score interpretations using different measures specific to each of the theoretical models. This paper examined Messick's notion (1989) of the validity of test-score interpretations as applied to three of the most widely used measures derived under each of the three different theoretical models of self-concept. Results suggest that overall multidimensional measures are more consistent in classifying individual's self-concept than unidimensional measures.