Rethinking the Control of Nuisance Variables in Theory Testing

In testing hypotheses, researchers frequently have used multiple regression analysis to control for nuisance variables (i.e., potential confounding variables that are correlated with hypothesized causal variables). In this paper, we highlight limitations of this control strategy, and we discuss fundamental issues that should be considered in deciding whether to use it. Ultimately, we suggest the use of multiple regression analysis sometimes may not improve causal understanding and may actually limit the generalizability of results. Instead of the common practice of controlling for nuisance variables, we suggest that looking at shared variance frequently is a more appropriate test of a theoretical hypothesis.     

Relational Diagnosis: A Retrospective Synopsis

This article highlights and summarizes efforts that have been made primarily during the past 20 years to bring the significance of relational diagnosis to the attention of the entire mental health community, and either (1) to have dysfunctional relational interactive patterns classified and codified and accepted for inclusion in the Diagnostic and Statistical Manual of Mental Disorders, or (2) if this is not feasible, to have a nosology of relational diagnoses, which have been clearly defined with accompanying risks specified for mental illnesses that might develop, and criteria sets delineated and adequately field tested to warrant and lead to publication of a separate but equal Diagnostic Manual of Relational Disorders and Dysfunctional Interactional Patterns.     

The relationship of thought-action fusion to pathologicial worry and generalized anxiety disorder

Meta-cognitive beliefs associated with pathological worry and generalized anxiety disorder (GAD) may encompass the likelihood subtype of thought-action fusion (TAF), the belief that one's thoughts can influence outside events. In the current study of 494 undergraduate college students, positive correlations between scores on the Penn State Worry Questionnaire (PSWQ) and the two Likelihood subscales of the TAF Scale were found, and participants endorsing at least some DSM-IV diagnostic criteria for GAD scored significantly higher on both TAF-Likelihood subscales than participants reporting no GAD symptoms. However, these TAF scales did not predict GAD diagnostic status with PSWQ included as a predictor. In contrast to previous research, the TAF-Moral scale did not correlate with worry. Relationships between TAF, pathological worry, and meta-cognition are discussed in relation to GAD.     

Cue abstraction and ideal prototype abstraction in estimation tasks

This study investigates abstracted processes and introduces a new prototype abstraction model adapted to estimation tasks. This prototype abstraction model assumes that the processing of whole exemplar patterns supports the detection of the underlying statistics necessary for the abstraction of two extreme prototypes on the continuous criterion dimension of the task. The prototypes are stored in memory as valid reference points for future similarity-based judgments. This prototype model was compared with the cue abstraction model, which assumes that people abstract cue weights in learning and add the cue information from exemplars to infer their criterion values varying on the continuous dimension. This study hypothesises that the training mode and the number of exemplars in training interact and affect subsequent model performance at test. The results from an experiment confirmed this hypothesis and showed that observational training supports an efficient prototype abstraction and feedback training supports an efficient cue abstraction.     

Evaluating interobserver reliability of interval data

Previous recommendations to employ occurrence, nonoccurrence, and overall estimates of interobserver reliability for interval data are reviewed. A rationale for comparing obtained reliability to reliability that would result from a random-chance model is explained. Formulae and graphic functions are presented to allow for the determination of chance agreement for each of the three indices, given any obtained per cent of intervals in which a response is recorded to occur. All indices are interpretable throughout the range of possible obtained values for the per cent of intervals in which a response is recorded. The level of chance agreement simply changes with changing values. Statistical procedures that could be used to determine whether obtained reliability is significantly superior to chance reliability are reviewed. These procedures are rejected because they yield significance levels that are partly a function of sample sizes and because there are no general rules to govern acceptable significance levels depending on the sizes of samples employed.     

A SIMPLIFIED TIME-SERIES ANALYSIS FOR EVALUATING TREATMENT INTERVENTIONS

Time-series analysis procedures for analyzing behavioral data are receiving increasing support. However, several authorities strongly recommend using at least 50–100 points per experimental phase. A complex mathematical model must then be empirically developed using computer programs to extract serial dependency from the data before the effects of treatment interventions can be evaluated. The present discussion provides a simple method of evaluating intervention effects that can be used with as few as 8 points per experimental phase. The calculations are easy enough to do by hand.     

The stability and clinical significance of distress: A rejoinder to pepper and coyne

Past research has established that some individuals with high Beck Depression Inventory (BDI) scores at one time point have scores that are lower at a second time point. Recently, we provided evidence indicating that the temporal instability of certain BDI scores may be due partly to the regression to the mean phenomenon. Pepper and Coyne (1996) question this statistical interpretation; they argue that distress among students is unstable for substantive reasons. In the current paper, we reaffirm our view that statistical and measurement factors may account, in part, for changes in BDI scores over time. Given this possibility, inferences about distress or depression as a latent construct in student samples are not warranted if these inferences are based on the administration of a single instrument such as the BDI; any conclusions about distress as a psychological construct must be qualified by acknowledging the possible roles of error and method variance. Clearly, empirical research is needed in order to obtain a better understanding of the nature of distress as a latent variable, especially in light of evidence which indicates that subthreshold levels of depression have a high degree of clinical significance.     

Assessing local influence for specific restricted likelihood: Application to factor analysis

In restricted statistical models, since the first derivatives of the likelihood displacement are often nonzero, the commonly adopted formulation for local influence analysis is not appropriate. However, there are two kinds of model restrictions in which the first derivatives of the likelihood displacement are still zero. General formulas for assessing local influence under these restrictions are derived and applied to factor analysis as the usually used restriction in factor analysis satisfies the conditions. Various influence schemes are introduced and a comparison to the influence function approach is discussed. It is also shown that local influence for factor analysis is invariant to the scale of the data and is independent of the rotation of the factor loadings. The authors are most grateful to the referees, the Associate Editor, and the Editor for helpful suggestions for improving the clarity of the paper.     

检验能力对统计显著性检验的影响

利用计算机构造被试总体、模拟实验研究程序进行抽样研究,探讨抽样样本总体达到t检验显著性的数目与统计检验能力之间的一致性。模拟实验结果表明,统计检验能力与样本总体t检验显著性的数目具有很高的一致性,但两者同时受到显著性水平α、样本客量n和总体效果大小δ的影响,从而有可能影响统计推断的可靠性。因此,在进行显著性检验过程中,应对统计检验能力进行估计,这将有利于心理学研究成果的积累。