Reflections on the statistical analysis of personality and norms in war, peace, and prejudice: Are deviant minorities the problem?

The compelling quality of the Global Change simulation study (Altemeyer, 2003), in which high RWA (right-wing authoritarianism)/high SDO (social dominance orientation) individuals produced poor outcomes for the planet, rests on the inference that the link between high RWA/SDO scores and disaster in the simulation can be generalized to real environmental and social situations. However, we argue that studies of the Person × Situation interaction are biased to overestimate the role of the individual variability. When variables are operationalized, strongly normative items are excluded because they are skewed and kurtotic. This occurs both in the measurement of predictor constructs, such as RWA, and in the outcome constructs, such as prejudice and war. Analyses of normal linear statistics highlight personality variables such as RWA, which produce variance, and overlook the role of norms, which produce invariance. Where both normative and personality forces are operating, as in intergroup contexts, the linear analysis generates statistics for the sample that disproportionately reflect the behavior of the deviant, antinormative minority and direct attention away from the baseline, normative position. The implications of these findings for the link between high RWA and disaster are discussed.

The normative ontology of the law - Peter Cane's responsibility in law and morality

Implications of Peter Cane's analysis of responsibility in 'Responsibility in Law and Morality' - Cane's preconceptualisation of the 'symbiotic' relationship between law and morality - a principal criticism is that Cane does not develop his seven methodological principles into a more ambitious argument.

Normative influence and rational conflict decisions: Group norms and cost-benefit analyses for intergroup behavior

The present paper articulates a model in which ingroup and outgroup norms inform 'rational' decision-making (cost-benefit analysis) for conflict behaviors. Norms influence perceptions of the consequences of the behavior, and individuals may thus strategically conform to or violate norms in order to acquire benefits and avoid costs. Two studies demonstrate these processes in the context of conflict in Quebec. In the first study, Anglophones' perceptions of Francophone and Anglophone norms for pro-English behaviors predicted evaluations of the benefits and costs of the behaviors, and these cost-benefit evaluations in turn mediated the norm-intention links for both group norms. In the second study, a manipulated focus on supportive versus hostile ingroup and outgroup norms also predicted cost-benefit evaluations, which mediated the norm-intention relationships. The studies support a model of strategic conflict choices in which group norms inform, rather than suppress, rational expectancy value processes. Implications for theories of decision-making and normative influence are discussed.

Explaining landholders' decisions about riparian zone management: The role of behavioural, normative, and control beliefs

Water quality is a key concern in the current global environment, with the need to promote practices that help to protect water quality, such as riparian zone management, being paramount. The present study used the theory of planned behaviour as a framework for understanding how beliefs influence decisions about riparian zone management. Respondents completed a survey that assessed their behavioural, normative, and control beliefs in relation to intentions to manage riparian zones on their property. The results of the study showed that, overall, landholders with strong intentions to manage their riparian zones differed significantly in terms of their beliefs compared to landholders who had weak intentions to manage their riparian zones. Strong intentions to manage riparian zones were associated with a favourable cost-benefit analysis, greater perceptions of normative support for the practice and lower perceptions of the extent to which barriers would impede management of riparian zones. It was also evident that willingness to comply with the recommendations of salient referents, beliefs about the benefits of riparian zone management and perceptions of the extent to which barriers would impede riparian zone management were most important for determining intentions to manage riparian zones. Implications for policy and extension practice are discussed. (c) 2005 Elsevier Ltd. All rights reserved.

Tympanometric findings in children at school entry: A normative study

This study presents tympanometric normative data for Australian children at school entry in view of the lack of age-specific population-based data for this group. Participants were 327 children (164 boys, 163 girls) aged between 5 and 6 years, who had no history of middle ear infection, and passed pure-tone screening at 20 dB HL. Normative values for static admittance (SA), ear canal volume (ECV), tympanometric peak pressure, tympanometric width (TW) and tympanometric gradient were established. Based on these normative data, the use of the ASHA (1997) guidelines for medical referral, in which ECV > 1.0 ml in the presence of a flat tympanogram, SA < 0.3 ml, or TW > 200 daPa may not provide the best criteria for Australian children aged between 5 and 6 years. If SA < 0.3 ml were used instead of SA < 0.16 ml, a greater proportion of Australian children would have failed tympanometry, thus increasing the false alarm rate.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.