Exploring MMPI-Rorschach relationships

Limitations exist in the current literature examining Minnesota Multiphasic Personality Inventory (MMPI)-Rorschach interrelationships. In this article I attempt to identify several issues to be addressed by researchers in this area. These include restricting conclusions about MMPI-Rorschach relationships to research using the Comprehensive System; considering the relative reliability and validity of these tests; comparing the predictive power of the Rorschach and MMPI; examining the effects extreme outliers have on statistical analyses; and determining the appropriate level of analysis for research, the level of individual test scores, or psychological constructs. The implications of these issues for research design, statistical analysis, and applied clinical work are discussed.     

Exploring MMPI-Rorschach Relationships

Limitations exist in the current literature examining Minnesota Multiphasic Personality Inventory (MMPI)—Rorschach interrelationships. In this article I attempt to identify several issues to be addressed by researchers in this area. These include restricting conclusions about MMPI—Rorschach relationships to research using the Comprehensive System; considering the relative reliability and validity of these tests; comparing the predictive power of the Rorschach and MMPI; examining the effects extreme outliers have on statistical analyses; and determining the appropriate level of analysis for research, the level of individual test scores, or psychological constructs. The implications of these issues for research design, statistical analysis, and applied clinical work are discussed.     

Some results on extensions and modifications of the Theil — Sen regression estimator

Many robust regression estimators have been proposed that have a high, finite‐sample breakdown point, roughly meaning that a large porportion of points must be altered to drive the value of an estimator to infinity. But despite this, many of them can be inordinately influenced by two properly placed outliers. With one predictor, an estimator that appears to correct this problem to a fair degree, and simultaneously maintain good efficiency when standard assumptions are met, consists of checking for outliers using a projection‐type method, removing any that are found, and applying the Theil — Sen estimator to the data that remain. When dealing with multiple predictors, there are two generalizations of the Theil — Sen estimator that might be used, but nothing is known about how their small‐sample properties compare. Also, there are no results on testing the hypothesis of zero slopes, and there is no information about the effect on efficiency when outliers are removed. In terms of hypothesis testing, using the more obvious percentile bootstrap method in conjunction with a slight modification of Mahalanobis distance was found to avoid Type I error probabilities above the nominal level, but in some situations the actual Type I error probabilities can be substantially smaller than intended when the sample size is small. An alternative method is found to be more satisfactory.     

Incremental Validity of Perceived Control Dimensions in the Differential Prediction of Interpretive Biases for Threat

This study evaluated whether a diminished perception of control over environmental and interoceptive events differentially predicted interpretive biases for threat for ambiguous scenarios. The sample had 95 participants without a history of psychopathology. Results indicated that the internal dimension of the Anxiety Control Questionnaire (ACQ; R. M. Rapee, M. G. Craske, T. A. Brown, & D. H. Barlow, 1996) was predictive of interpretive biases for internal scenarios above and beyond demographic variables, subclinical panic attack history, and state anxiety; the external control subscale of the ACQ also was predictive of internal rank-ordered responses. The ACQ external dimension was predictive of interpretive responses for external scenarios beyond the effects accounted for by the other predictor variables, including perceived control for internal events. These findings provide initial correlational evidence consistent with cognitive–behavioral accounts of panic disorder that posit a perceived lack of control over aversive events may exacerbate an interpretive bias for threat.     

Sustained attention in children at risk for schizophrenia: Findings with two visual continuous performance tests in a new sample

In partial replication of an earlier study, 35 children at high risk for schizophrenia, 25 children at high risk for affective disorder, and 53 normal control children from a new sample of 7- to 12-year-old subjects were tested with two new visual continuous performance tests. Response levels and intrasubject variability were analyzed separately. Multivariate analyses on factor scores derived from response levels indicate that "groups" is a significant predictor for a factor reflecting discriminability (or sensitivity) for the more difficult of these tests but not for the less difficult one, and that high risk for schizophrenia is associated with lower performance. Factor scores and multiple regression analyses were used to dichotomize subjects as to whether or not they are low performance outliers. A significantly larger proportion of subjects from the high risk for schizophrenia group than from the control groups were low performance outliers. Among subjects that developed psychopathology in adolescence, subjects at high risk for schizophrenia were more likely to have contributed low performance outliers early during childhood.     

A Psychometric Evaluation of the Approach and Avoidance of Alcohol Questionnaire Among Alcohol-Dependent Patients Attending Residential Treatment

Despite research suggesting that alcohol-dependent individuals have both craving and avoidant tendencies for alcohol, few studies have measured self-report tendencies using the Approach and Avoidance of Alcohol Questionnaire (AAAQ). The goal of this study was to examine the psychometric properties of the AAAQ using a sample of adults receiving 12 step-based residential treatment for alcohol dependence. As part of a larger study, 100 adults receiving residential treatment completed the AAAQ and several other assessments shortly after treatment admission. Analyses of the AAAQ examined its factor structure, internal consistency, and convergent and predictive validity. A maximum likelihood estimation factor analysis using oblique rotation produced 3 factors accounting for 69 % of the variance. A confirmatory factor analysis suggested that the 3-factor model was a moderate fit for data from a second sample of patients. Internal consistency was fairly high and convergent validity was demonstrated by relationships with another scale of alcohol craving, time since last drink, and quantity and frequency of pre-treatment alcohol use. Regarding predictive validity, the level of approach tendencies on the AAAQ was significantly related to abstinence status during the first 6 months following treatment. Avoidance level was not related to abstinence. The results largely replicated past studies utilizing outpatient samples and suggest that the AAAQ shows promise as a psychometrically sound, internally reliable self-report craving measure for individuals with alcohol dependence.     

Comparing one-step m-estimators of location corresponding to two independent groups

Experience with real data indicates that psychometric measures often have heavy-tailed distributions. This is known to be a serious problem when comparing the means of two independent groups because heavy-tailed distributions can have a serious effect on power. Another problem that is common in some areas is outliers. This paper suggests an approach to these problems based on the one-step M-estimator of location. Simulations indicate that the new procedure provides very good control over the probability of a Type I error even when distributions are skewed, have different shapes, and the variances are unequal. Moreover, the new procedure has considerably more power than Welch's method when distributions have heavy tails, and it compares well to Yuen's method for comparing trimmed means. Wilcox's median procedure has about the same power as the proposed procedure, but Wilcox's method is based on a statistic that has a finite sample breakdown point of only 1/n, wheren is the sample size. Comments on other methods for comparing groups are also included.     

South Asian women: identities and conflicts

This study investigated the effects of education, level of religiosity, ethnic identity (internal and external), and racial identity statuses (conformity, dissonance, resistance, and awareness) on cultural value conflict for first and second generation South Asian women (N = 193). Cultural value conflict was examined in two areas, intimate relations and sex-role expectations. Results revealed that level of religiosity was more predictive of intimate relations conflict for second generation than first generation women. Furthermore, higher ratings in internal ethnic identity predicted greater intimate relations conflict in first generation women, while both internal and external ethnic identity predicted intimate relations conflict in second generation women. Finally, higher dissonance scores in racial identity predicted greater conflicts in sex-role expectations for second generation women alone.     

姿势干扰强度的心理预期效应

本研究基于经典快速举臂试验与落球试验范式, 采用表面肌电信号分析技术, 研究内、外姿势干扰强度的心理预期对腰部姿势肌肉和上肢动作肌肉预期姿势调节(APAs)和补偿姿势调节(CPAs)的影响, 探讨中枢神经系统(CNS)对内、外姿势干扰的控制策略。20名健康受试者先后完成不同负荷强度的快速举臂试验和落球试验, 同步采集腰部竖脊肌、腰部多裂肌和上肢肱二头肌的表面肌电信号, 计算肌肉预激活时间和APAs与CPAs积分肌电值, 观察内、外姿势干扰强度的心理预期对中枢APAs和CPAs控制机制的影响。结果显示内部姿势干扰条件下, 干扰强度的心理预期对腰部多裂肌、腰部竖脊肌和上肢肱二头肌的APAs强度有显著影响, 而对预激活时间和CPAs强度无显著影响; 外部姿势干扰条件下, 干扰强度的心理预期对腰部多裂肌、腰部竖脊肌和肱二头肌的APAs强度有显著影响, 对肱二头肌和腰部多裂肌预激活时间有显著影响, 而对CPAs强度无显著影响。突发可预期姿势干扰条件下姿势的快速反应是一个由CNS主导的神经肌肉运动控制过程。受姿势干扰强度心理预期的影响, CNS对内、外突发姿势干扰条件下腰部姿势肌肉的活动采取了不同的控制策略。在内部姿势干扰条件下, 干扰刺激发生时间明确, CNS主要通过对APAs强度的调节来实现姿势肌肉的优化控制; 而在外部姿势干扰条件下, 干扰刺激时间不明确, CNS则通过对局部稳定肌APAs预激活时间以及局部稳定肌和整体稳定肌APAs强度的双重调节实现姿势肌肉的优化控制。干扰强度的心理预期对姿势肌肉APAs和CPAs的作用表明, 心理预期效应主要源自于CNS对局部和整体稳定肌APAs控制机制的调制。     

Do group-based mindfulness meditation programs enhance executive functioning? A systematic review and meta-analysis of the evidence

Research examining the effects of group-based mindfulness interventions on executive functioning have yielded inconsistent findings, with some reports of enhanced performance and other reports of null findings. Inconsistencies in the literature may be due to methodological differences across studies, including the type of control group employed and sample characteristics (e.g., clinical vs. non-clinical samples). The current systematic review and meta-analysis examined the effect of group-based mindfulness programs on executive functioning in persons 18+ years of age. Following the standards for systematic review, a total of 29 studies were included in the meta-analysis, of which 21 comparisons contributed to the analysis of inhibition; nine to working memory; nine to attention shifting; and four to the analysis of verbal fluency. After removing outliers, random effects models suggested a small but significant synthesized effect of group-mindfulness training on overall executive functioning (95% CI = 0.256, 0.725). Examination of executive subdomains after removing outliers suggested a small, statistically significant effect for inhibition (95% CI = 0.055, 0.387), working memory (95% CI = 0.010, 0.437), and verbal fluency (95% CI = 0.071, 1.931). No significant pooled effects were found for attention shifting. A priori subgroup analysis by randomization, type of control group, and sample cohort revealed inconsistent results. Overall, the current review suggests that the effect of group-based mindfulness training on executive functioning is not robust.     

Study samples are too small to produce sufficiently precise reliability coefficients

In a survey of journal articles, test manuals, and test critique books, the author found that a mean sample size (N) of 260 participants had been used for reliability studies on 742 tests. The distribution was skewed because the median sample size for the total sample was only 90. The median sample sizes for the internal consistency, retest, and interjudge reliabilities were 182, 64, and 36, respectively. The author presented sample size statistics for the various internal consistency methods and types of tests. In general, the author found that the sample sizes that were used in the internal consistency studies were too small to produce sufficiently precise reliability coefficients, which in turn could cause imprecise estimates of examinee true-score confidence intervals. The results also suggest that larger sample sizes have been used in the last decade compared with those that were used in earlier decades.     

Modern Molar Behaviorism And Theoretical Behaviorism: Religion And Science.

Baum and staddon disagree on the status of internal states in behavior analysis. Baum advocates molar behaviorism, treating behavior in temporally extended segments and so avoiding the need for internal states. Staddon argues that internal states merely represent the effects of different histories and that their use brings behavior analysis in line with the established sciences. The dispute is one form of the age‐old molar—molecular controversy that characterized Aristotle's disagreement with Plato. Both molar and molecular analyses have their place, but molar behaviorism may apply more naturally to a variety of phenomena, ranging from the matching law and avoidance learning to socalled “higher mental processes.” When molecular analysis involves internal states, as in Staddon's Theoretical Behaviorism (or New Behaviorism), misunderstanding will be inevitable and behaviorism will be seen as one more instance of the mediational theories in which psychology has long been mired. Such theories have long dominated the physical sciences, where their usefulness is indisputable, but psychology is far behind the physical sciences and nonmediational molar behaviorism better suits a discipline that lacks the methods and the data of the established sciences.     

Accommodating Small Sample Sizes in Three-Level Models When the Third Level is Incidental

Small samples sizes are a pervasive problem when modeling clustered data. In two-level models, this problem has been well studied, and several resources provide guidance for modeling such data. However, a recent review of small-sample clustered data methods has noted that no studies have investigated methods for modeling three-level data with small sample sizes. Furthermore, strategies for two-level models do not necessarily translate to the three-level context. Moreover, three-level models are prone to small samples because the “small sample” designation is primarily based on the sample size of the highest level, and large samples are increasingly difficult to amass as one progresses up a hierarchy. In this study, we focus on the case when the third level is incidental, meaning that the third level is important to consider but there are no explicit research questions at the third level. This study performs a simulation study to examine the performance of seven methods for modeling three-level data with a small sample at the third level. A motivating educational psychology example is also provided to demonstrate how the choice of method can greatly affect results.     

The Development and Validation of the Memory Support Treatment Provider Checklist

Patient memory for the contents of treatment is staggeringly poor, and poor memory for treatment is associated with worse treatment outcome. Accordingly, the Memory Support Intervention was developed to improve patient memory for treatment as an adjunct to treatment as usual. As plans to disseminate the Memory Support Intervention are developed, it is important to have efficient, accurate methods of measuring fidelity to the intervention. However, the existing method of assessing fidelity to the Memory Support Intervention, the Memory Support Rating Scale (MSRS), is burdensome and requires trained independent-raters to spend multiple hours reviewing session recordings, which is not feasible in many routine mental health care settings. Hence, a provider-rated measure of fidelity to the MSI has been developed. The goal of this study is to examine the reliability and validity of scores on this measure—the Memory Support Treatment Provider Checklist. A sample of Memory Support Treatment Provider Checklists (N = 319) were completed by providers (N = 8) treating adults with depression (N = 84). Three metrics of the Memory Support Treatment Provider Checklist were evaluated: (a) the internal consistency and structural validity using confirmatory factor analysis based on prior research on the MSRS and the Memory Support Intervention, (b) construct validity, and (c) predictive validity. Results indicate that the Memory Support Treatment Provider Checklist yields reliable and valid scores of fidelity to the Memory Support Intervention. Overall, this checklist offers a viable, brief method of evaluating fidelity to the Memory Support Intervention.     

Mindfulness and mind wandering: The protective effects of brief meditation in anxious individuals

Mind wandering can be costly, especially when we are engaged in attentionally demanding tasks. Preliminary studies suggest that mindfulness can be a promising antidote for mind wandering, albeit the evidence is mixed. To better understand the exact impact of mindfulness on mind wandering, we had a sample of highly anxious undergraduate students complete a sustained-attention task during which off-task thoughts including mind wandering were assessed. Participants were randomly assigned to a meditation or control condition, after which the sustained-attention task was repeated. In general, our results indicate that mindfulness training may only have protective effects on mind wandering for anxious individuals. Meditation prevented the increase of mind wandering over time and ameliorated performance disruption during off-task episodes. In addition, we found that the meditation intervention appeared to promote a switch of attentional focus from the internal to present-moment external world, suggesting important implications for treating worrying in anxious populations.     

Order‐constrained linear optimization

Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order‐constrained linear least‐squares (OCLO) optimization algorithm that maximizes the linear least‐squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out‐of‐sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat‐tailed distributions), OCLO shows less bias and variance, and substantially better out‐of‐sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data.     

Modern Regression Methods that can Substantially Increase Power and Provide a more Accurate Understanding of Associations

During the last half century, hundreds of papers published in statistical journals have documented general conditions where reliance on least squares regression and Pearson's correlation can result in missing even strong associations between variables. Moreover, highly misleading conclusions can be made, even when the sample size is large. There are, in fact, several fundamental concerns related to non‐normality, outliers, heteroscedasticity, and curvature that can result in missing a strong association. Simultaneously, a vast array of new methods has been derived for effectively dealing with these concerns. The paper (i) reviews why least squares regression and classic inferential methods can fail, (ii) provides an overview of the many modern strategies for dealing with known problems, including some recent advances, and (iii) illustrates that modern robust methods can make a practical difference in our understanding of data. Included are some general recommendations regarding how modern methods might be used. Copyright © 2011 John Wiley & Sons, Ltd.     

OUTLIER DETECTION AND TREATMENT IN I/O PSYCHOLOGY: A SURVEY OF RESEARCHER BELIEFS AND AN EMPIRICAL ILLUSTRATION

Extreme data points, or outliers, can have a disproportionate influence on the conclusions drawn from a set of bivariate correlational data. This paper addresses two aspects of outlier detection. The results of a survey regarding how published researchers prefer to deal with outliers are presented, and a set of 183 test validity studies is examined to document the effects of different approaches to the detection and exclusion of outliers on effect size measures. The study indicates that: (a) there is disagreement among researchers as to the appropriateness of deleting data points from a study; (b) researchers report greater use of visual examination of data than of numeric diagnostic techniques for detecting outliers; and (c) while outlier removal influenced effect size measures in individual studies, outlying data points were not found to be a substantial source of variance in a large test validity data set.     

Activities, self-referent memory beliefs, and cognitive performance: evidence for direct and mediated relations

In this study, the authors investigated the role of activities and self-referent memory beliefs for cognitive performance in a life-span sample. A factor analysis identified 8 activity factors, including Developmental Activities, Experiential Activities, Social Activities, Physical Activities, Technology Use, Watching Television, Games, and Crafts. A second-order general activity factor was significantly related to a general factor of cognitive function as defined by ability tests. Structural regression models suggested that prediction of cognition by activity level was partially mediated by memory beliefs, controlling for age, education, health, and depressive affect. Models adding paths from general and specific activities to aspects of crystallized intelligence suggested additional unique predictive effects for some activities. In alternative models, nonsignificant effects of beliefs on activities were detected when cognition predicted both variables, consistent with the hypothesis that beliefs derive from monitoring cognition and have no influence on activity patterns.