Note on computation of bi-serial correlations in item evaluation

By the use of an algebraic variant of the ordinary formula for bi-serial correlation, tables, and graphic devices, a time-saving systematic procedure for the computation of bi-serial correlation co-efficients is outlined for application to the evaluation of items of a test. A table of z for arguments ofp=.000 top=.999 is given.     

INCREASING THE INDEPENDENT RESPONDING OF AUTISTIC CHILDREN WITH UNPREDICTABLE SUPERVISION

We investigated the role of predictable versus unpredictable supervision on the independent task responding of three autistic children. In a predictable supervision condition, the therapist was present in the setting for a regular period of time and then was absent for the remainder of the session. In an unpredictable supervision condition, the therapist's presence was scheduled on a random, intermittent, and unpredictable basis throughout the session. The multiple baseline analysis showed that the unpredictable supervision produced much higher levels of on-task responding during the therapist's absence for all three children. Analysis of work completed during the therapist's absence also favored the unpredictable supervision condition. The results are discussed in relation to the literature on generalization and educational practice.     

International publication trends of JABA authorship

The present study addressed international publication trends in JABA authorship between 1970 and 1999. First, we analyzed authorship patterns to identify trends in the appearance of new first authors, unfamiliar authors, and frequent contributors. Second, articles were assigned to either a North American or an international category. The data show a decline in the number of articles by new authors and an increase in the publications of frequent contributors from North America. Trends are shown in comparison to those from the American Journal on Mental Retardation.     

A program to compute McGraw and wong’s common language effect size indicator

McGraw and Wong (1992) have described a very appealing index of effect size that requires no prior knowledge of statistics to understand, which they termed CL, the common language effect size indicator. CL is the probability that a score randomly sampled from one distribution will be larger than a randomly sampled score from a second distribution. McGraw and Wong describe how to compute CL from the means and standard deviations of two groups, using tables of normal curve probability values. The program described herein computes CL without lookup tables but also permits the user to compute CL from Cohen’s d, from a t test for independent groups, or from point-biserial r, the correlation between a dichotomous and a continuous variable. A table giving CL for various values of d is also provided, as are the equations for converting t and r to d.     

Communality of videogame performances with tracking tasks

Performances on three videogames were compared with two different tracking tasks and a third dual tracking task, after stability of performance was achieved by 40 male subjects. The six tasks were performed in succession for three weeks each, and one year separated administration of the tracking tasks from the videogames. Convergence of the cross-correlations among these tasks occurred such that higher correlations were attained for scores obtained late in practice (late/late) of two tasks (even when they were performed a year apart) rather than for scores obtained earlier in training (viz., early/early). High communality between these two types of tasks was observed as indicated by virtual overlap between the videogames and the tracking tasks, even though different control media (joysticks, knobs), control orders (zero/first), and control inputs (displacement/force transducer) were required. Because these tasks apparently index similar abilities, there may be advantages to measuring tracking skills with videogames, which include low cost, wide availability, inherent interest to subjects and motivation, rapid approach to stable levels, and, in many cases greater apparent face validity relative to real world performance requirements.     

Conservatism positively predicted fading affect bias in the 2016 US presidential election at low,but not high,levels of negative affect

Unpleasant affect fades faster than pleasant affect and this Fading Affect Bias (FAB) phenomenon is positively related to healthy outcomes and negatively related to unhealthy outcomes, which makes the FAB a healthy coping process/reaction. Rehearsal seems to be the cognitive mechanism responsible for the FAB. Although the FAB and its relation to healthy outcomes and rehearsal have been examined in many contexts, they have not been evaluated in the realm of politics. Therefore, we evaluated the FAB across event type and we examined the relation of FAB to political leaning (conservatism), unhealthy variables, healthy variables, and rehearsal for the 2016 US Presidential Election. We expected and found that FAB was larger for non‐political events than for election/political events, and conservatism positively predicted FAB. We also expected and found that unhealthy/healthy outcome variables related to FAB in predictable ways. Importantly, we found that negative affect moderated the relation of FAB and conservatism, and rehearsal ratings mediated this 3‐way interaction. The results supported emotion regulation models, such as the mobilization‐minimization hypothesis and self‐enhancement theory.     

The Spurious Correlation of Ratios that Have Common Variables: A Monte Carlo Examination of Pearson's Formula

Pearson (1897) investigated correlations of ratios of bone measurements and found that although the correlations among the original measures were low, the correlations among ratios with common measures were about .5. To understand this result, he developed an approximate equation for the correlations of ratios. In the present study, Monte Carlo methods were used to show that Pearson's equation is fairly accurate and that correlations among ratios with common elements (e.g., X/C, Y/C) are indeed at least partly spurious, as Pearson concluded. This finding should serve as a two-fold warning to those who might correlate ratios that have common elements: (a) Interpretation of the observed relationship between such ratios may at best be tenuous, and (b) the relationships among the elements themselves may call into question the usefulness of addressing a hypothesis that can be tested only with a correlation between ratios that share elements.