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Psychophysiologists often use repeated measures analysis of variance (RMANOVA) and multivariate analysis of variance (MANOVA) to analyze data collected in repeated measures research designs. ANOVA and MANOVA are nomothetic approaches that focus on group means. Newer multilevel modeling techniques are more informative than ANOVA because they characterize both group-level (nomothetic) and individual-level (idiographic) effects, yielding a more complete understanding of the phenomena under study. This article was written as an introduction to growth curve modeling for applied researchers. A growth model is defined that can be used in place of RMANOVAs and MANOVAs for single-group and mixed repeated measures designs. The model is expanded to test and control for the effects of baseline levels of physiological activity on stimulus-specific responses. Practical, conceptual, and statistical advantages of growth curve modeling are discussed.

Evidence-based practice approaches to interventions has come of age and promises to provide a new standard of excellence for school psychologists. This article describes several definitions of evidence-based practice and the problems associated with traditional statistical analyses that rely on rejection of the null hypothesis for the establishment of invention effectiveness. Metaanalysis as an approach to ascertain EBPs is reviewed along with the inherent difficulties associated with single subject design research such as autocorrelations. Four meta-analytic approaches are reviewed which include Percentage of Nonoverlapping Data points (PND), the Busk and Serlin: Assumption models, ITSACORR, and Hierarchical Linear Modeling (HLM). HLM is offered as the most promising approach for the analysis for single subject designs. Monte Carlo simulations are modeled with varying degrees of autocorrelations, differing numbers of data points, and simulated effects sizes to show that HLM is an acceptable approach for controlling the risk of Type I errors.

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Background We sought to apply modified labeling theory in a cross-sectional study of alcohol use disorder (AUD) to investigate the mechanisms through which perceived alcohol stigma (PAS) may lead to the persistence of AUD and risk of psychiatric disorder. Methods We conducted structural equation modeling (SEM) including moderated mediation analyses of two waves (W1 and W2) of data from the National Epidemiologic Survey on Alcohol and Related Conditions. We analyzed validated measures of PAS, perceived social support, social network involvement, and psychiatric disorders among (n = 3608) adults with two or more DSM-5 AUD symptoms in the first two of the three years between the W1 and W2 survey. Cross-sectional analyses were conducted owing to the assessment of PAS only at W2. Results Per mediation analyses, lower levels of perceived social support explained the association of PAS with past-year AUD and past-year internalizing psychiatric disorder at W2. The size of the mediated relationship was significantly larger for those classified as labeled (i.e., alcoholic) per their prior alcohol treatment or perceived need (n = 938) as compared to unlabeled (n = 2634), confirming a hypothesis of moderated mediation. Unexpectedly, mediation was also present for unlabeled individuals. Conclusions Lower levels of social support may be an important intermediate outcome of alcohol stigma. Longitudinal data are needed to establish the temporal precedence of PAS and its hypothesized intermediate and distal outcomes. Research is needed to evaluate direct measures of labeling that could replace proxy measures (e.g., prior treatment status) commonly employed in studies of the stigma of psychiatric disorders.

Introduction There has been an increasing interest in studying the stigma of alcohol use disorders (AUDs) yet scant research has evaluated the conceptualization and measurement of alcohol stigma. This study examined the measurement properties (i.e. factor structure) and validity of the alcohol-adapted Perceived Devaluation-Discrimination scale (PDD), which assesses the construct of perceived alcohol stigma (PAS). Materials and Methods Our sample included 34,386 respondents from the Wave 2 assessment in the National Epidemiologic Survey on Alcohol and Related Conditions, a population-representative survey of noninstitutionalized United States adults. Analytic procedures included confirmatory factor analysis and structural equation modeling. Results One factor (perceived devaluation-discrimination) and two factor (perceived devaluation, perceived discrimination) confirmatory factor analytic models fit the data well (CFI=0.958, TLI=0.942, RMSEA=0.056; CFI=0.962, TLI=0.946, RMSEA=0.054; respectively) when adjusting for item wording effects with a latent method factor. Despite having a better fit to the data (χ2(1) = 542, p < 0.0001), the two factors were highly correlated (r=0.90), which led us to favor a one-factor model. Structural equation models found that the inverse relationship between PAS and perceived interpersonal social support was strongest for persons with a stigmatized-labeling status. The same was not true in analyses predicting social network involvement. Conclusions A one-factor solution of perceived alcohol stigma had superior parsimony. The alcohol-adapted PDD appears to be a psychometrically sound measure and exhibits relationships that are consistent with modified labeling theory.

Our goal was to evaluate an alternative to current methods for detecting deception in security screening contexts. We evaluated a new cognitive-based test of deception that measured participants’ ocular-motor responses (pupil responses and reading behaviors) while they read and responded to statements on a computerized questionnaire. In Experiment 1, participants from a university community were randomly assigned to either a “guilty” group that committed one of two mock crimes or an “innocent” group that only learned about the crime. Participants then reported for testing, where they completed the computer-administered questionnaire that addressed their possible involvement in the crimes. Experiment 2 also manipulated participants’ incentive to pass the test and difficulty of statements on the test. In both experiments, guilty participants had increased pupil responses to statements answered deceptively; however, they spent less time fixating on, reading, and re-reading those statements than statements answered truthfully. These ocular-motor measures were optimally weighted in a discrimination function that correctly classified 85% of participants as either guilty or innocent. Findings from Experiment 2 indicated that group discrimination was improved with greater incentives to pass the test and the use of statements with simple syntax. The present findings suggest that two cognitive processes are involved in deception -- vigilance and strategy -- and that these processes are reflected in different ocular-motor measures. The ocular-motor test reported here represents a new approach to detecting deception that may fill an important need in security screening contexts.

The rapid evaluation of complex visual environments is critical for an organism's adaptation and survival. Previous studies have shown that emotionally significant visual scenes, both pleasant and unpleasant, elicit a larger late positive wave in the event-related brain potential (ERP) than emotionally neutral pictures. The purpose of the present study was to examine whether neuroelectric responses elicited by complex pictures discriminate between specific, biologically relevant contents of the visual scene and to determine how early in the picture processing this discrimination occurs. Subjects (n=264) viewed 55 color slides differing in both scene content and emotional significance. No categorical judgments or responses were required. Consistent with previous studies, we found that emotionally arousing pictures, regardless of their content, produce a larger late positive wave than neutral pictures. However, when pictures were further categorized by content, anterior ERP components in a time window between 200−600 ms following stimulus onset showed a high selectivity for pictures with erotic content compared to other pictures regardless of their emotional valence (pleasant, neutral, and unpleasant) or emotional arousal. The divergence of ERPs elicited by erotic and non-erotic contents started at 185 ms post-stimulus in the fronto-central midline regions, with a later onset in parietal regions. This rapid, selective, and content-specific processing of erotic materials and its dissociation from other pictures (including emotionally positive pictures) suggests the existence of a specialized neural network for prioritized processing of a distinct category of biologically relevant stimuli with high adaptive and evolutionary significance.