Proportion of third‐level variation in multi‐level studies: A note on an interval estimation procedure

An interval estimation procedure is outlined that can be used for evaluating the proportion of observed variance in a response variable, which is due to the third level of nesting in a hierarchical design. The approach is also useful when it is of concern to address the necessity of including a third level in analyses of data from a multi‐level study, relative to an alternative of proceeding with two‐level modelling. The proposed method is illustrated with an empirical example.     

Higher Order Factor Structure of the WISC-IV in a Clinical Neuropsychological Sample

A confirmatory factor analysis was conducted examining the higher order factor structure of the WISC-IV scores for 344 children who participated in neuropsychological evaluations at a large children's hospital. The WISC-IV factor structure mirrored that of the standardization sample. The second order general intelligence factor (g) accounted for the largest proportion of variance in the first-order latent factors and in the individual subtests, especially for the working memory index. The first-order processing speed factor exhibited the most unique variance beyond the influence of g. The results suggest that clinicians should not ignore the contribution of g when interpreting the first-order factors.     

The sensory‐cognition association in adulthood: Different magnitudes for processing speed,inhibition, episodic memory,and false memory?

One hundred and forty-six participants (age range = 20-80) completed a battery of tests designed to measure visual acuity, processing speed, inhibition, episodic memory and false memory. The relations between visual acuity and general cognitive ability, as well as between visual acuity and the indicators of this construct, were evaluated with structural equation modeling. The measurement model confirmed that the indicators of the individual cognitive abilities could be grouped into a general cognitive functioning factor. However, the relation between episodic and false memory was not completely explained by the shared association with this general factor. Furthermore, visual acuity predicted approximately half of the age-related variance in the general cognition factor. Also, the proportion of age-related variance shared with vision was highest in inhibition and lowest in false memory. The results are discussed in the light of common cause accounts of cognitive aging.     

General vs health‐specific consideration of immediate and future consequences to explain eating and exercise behavior in a Norwegian student population: A randomized survey experiment

Over several decades, the consideration of future consequences (CFC) construct has been used to explain and predict health behaviors. However, the reported associations between CFC and health behaviors are relatively weak, leading to the low explanatory power of the models. Recent research suggests that CFC can be a domain‐specific construct. In this study, we explored the psychometric properties of the Norwegian CFC‐general and CFC‐health questionnaires in terms of factor structure and discriminant and convergent validity and tested the association between the general and domain‐specific CFC and exercise and eating behaviors. In a randomized survey experiment, 1,001 university students were assigned to either a CFC‐general or a CFC‐health questionnaire. In the tested models, two dimensions of CFC, consideration of immediate consequences (CFC‐I) and consideration of future consequences (CFC‐F), were independent variables. The exercise and eating behaviors, measured both as self‐evaluated behaviors and self‐reported frequency measures, were dependent variables. The results showed that in both CFC‐general and CFC‐health, CFC‐I and CFC‐F are distinct dimensions that differentially explain variance in health behaviors. A domain‐specific CFC‐health explained a significantly higher amount of variance in self‐reported eating and exercising behaviors than a general CFC. Self‐evaluated health behaviors were better explained by CFC than self‐reported behavioral frequencies. Practical implications of the findings and avenues for future research are discussed.     

Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among a national sample of referred students

The structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; D. Wechsler, 2003a) was analyzed via confirmatory factor analysis among a national sample of 355 students referred for psychoeducational evaluation by 93 school psychologists from 35 states. The structure of the WISC-IV core battery was best represented by four first-order factors as per D. Wechsler (2003b), plus a general intelligence factor in a direct hierarchical model. The general factor was the predominate source of variation among WISC-IV subtests, accounting for 48% of the total variance and 75% of the common variance. The largest 1st-order factor, Processing Speed, only accounted for 6.1% total and 9.5% common variance. Given these explanatory contributions, recommendations favoring interpretation of the 1st-order factor scores over the general intelligence score appear to be misguided.     

Resisting Everything Except Temptation: Evidence and an Explanation for Domain‐specific Impulsivity

We propose a model of impulsivity that predicts both domain‐general and domain‐specific variance in behaviours that produce short‐term gratification at the expense of long‐term goals and standards. Specifically, we posit that domain‐general impulsivity is explained by domain‐general self‐control strategies and resources, whereas domain‐specific impulsivity is explained by how tempting individuals find various impulsive behaviours, and to a lesser extent, in perceptions of their long‐term harm. Using a novel self‐report measure, factor analyses produced six (non‐exhaustive) domains of impulsive behaviour (Studies 1–2): work, interpersonal relationships, drugs, food, exercise and finances. Domain‐general self‐control explained 40% of the variance in domain‐general impulsive behaviour between individuals, r_effect = .71. Domain‐specific temptation (r_effect = .83) and perceived harm (r_effect = ?.26) explained 40% and 2% of the unique within‐individual variance in impulsive behaviour, respectively (59% together). In Study 3, we recruited individuals in special interest groups (e.g. procrastinators) to confirm that individuals who are especially tempted by behaviours in their target domain are not likely to be more tempted in non‐target domains. Copyright © 2011 John Wiley & Sons, Ltd.     

A criterion for significant common factor variance

Up to the present only empirical methods have been available for determining the number of factors to be extracted from a matrix of correlations. The problem has been confused by the implicit attitude that a matrix of intercorrelations between psychological variables has a rank which is determinable. A table of residuals always contains error variance and common factor variance. The extraction of successive factors increases the proportion of error variance remaining to common factor variance remaining, and a point is reached where the extraction of more dimensions would contain so much error variance that the common factor variance would be overshadowed. The critical value for this point is determined by probability theory and does not take into account the size of the residuals. Interpretation of the criterion is discussed.     

Counterproductive behaviors: Relations across life domains,etiology, and implications for applied practice

Previous research on counterproductive work behavior (CWB) has shown that workplace deviance can be predicted from individual differences and environmental variables, but relatively little is known about CWBs’ relations with counterproductive behaviors in other domains of an individual's life. Data from 500 male twins were used to examine relations among counterproductive behaviors from several life domains, including school, non‐work, substance use, and work. The results supported the hypotheses that counterproductivity in work and a variety of personal life domains, previous and contemporaneous, are strongly and positively related. A general counterproductivity factor, giving rise to rule‐ and norm‐breaking behavioral repertoire of individuals, accounted for approximately half the variance across measures of counterproductivity in specific life domains. To inform theory and research, the etiology of inter‐individual differences in counterproductivity was examined. Biometric analyses revealed that most of the variance in the counterproductivity domains examined, including CWB, is attributable to genetic and unique (nonshared) environmental factors. The general counterproductivity factor spanning different counterproductivity domains was most influenced by genetic factors (75.4%), but was also influenced by unique environmental factors (24.6%). Biometric analyses indicated that 27% of the variance in CWB is attributable to genetic influences arising from the general factor of counterproductivity and 20% from genetic factors specific to CWB. Unique environmental influences associated with the work domain explained 12% of the variance in CWB. For the CWB criterion, regression analyses explored the usefulness of information from other counterproductivity domains for prediction and employee selection. Counterproductivity from academic and non‐work domains are potent predictors of counterproductivity at work (multiple Rs ranging between .50 and .54).     

测验同质性系数及其区间估计

在决定将多维测验分数合并成测验总分时, 应当考虑测验同质性。如果同质性太低, 合成总分没有什么意义。同质性高低可以用同质性系数来衡量。用来计算同质性系数的模型是近年来受到关注的双因子模型(既有全局因子又有局部因子), 测验的同质性系数定义为测验分数方差中全局因子分数方差所占的比例。本文用Delta法推导出计算同质性系数的标准误公式, 进而计算其置信区间。提供了简单的计算同质性系数及其置信区间的程序。用一个例子说明如何估计同质性系数及其置信区间, 通过模拟比较了用Delta法和用Bootstrap法计算的置信区间, 发现两者差异很小。     

Hierarchical Structure of Dysfunctional Beliefs in Obsessive‐Compulsive Disorder

The Obsessive Beliefs Questionnaire was developed as a comprehensive measure of dysfunctional beliefs, which cognitive models consider to be etiologically related to obsessive‐compulsive disorder. Obsessive Beliefs Questionnaire subscales tend to be highly correlated, which raises the question of whether obsessive‐compulsive‐related beliefs are hierarchically structured, consisting of lower‐order factors loading on 1 or more higher‐order factors. To investigate the nature and relative importance of these factors, a hierarchical factor analysis was conducted (n = 202 obsessive‐compulsive disorder patients), using a Schmid‐Leiman transformation. Results indicated a higher‐order (general factor) and 3 lower‐order factors: (i) responsibility and overestimation of threat, (ii) perfectionism and intolerance of uncertainty and (iii) importance and control of thoughts. The high‐order factor accounted for more variance in Obsessive Beliefs Questionnaire scores (22%) than did the lower‐order factors (6–7%), thereby underscoring the importance of the higher‐order factor. Despite the importance of the higher‐order factor, the lower‐order factors significantly predicted unique variance in measures of obsessive‐compulsive symptoms, including severity ratings of compulsions. These finding suggest that cognitive models of obsessive‐compulsive disorder should take into consideration the hierarchic structure of obsessive‐compulsive‐related beliefs.     

Reliability of multiple‐component measuring instruments: Improved evaluation in repeated measure designs

A covariance structure analysis method for improved point and interval estimation of composite reliability in repeated measure designs is outlined that accounts for specificity variance. The approach also permits the testing of time‐invariance in reliability of multiple‐component instruments in terms of the ratio of ‘pure’ measurement error variance to observed scale score variance. In addition, the procedure allows interval estimation of the difference in composite reliability coefficients across assessment occasions. The method described is illustrated with data from a cognitive intervention study.     

Evidence for a general factor of behavioral activation system sensitivity

Individual differences in one’s propensity to engage the behavioral activation system (BAS) and behavioral inhibition system (BIS) have primarily been studied with Caver and White’s (1994) BIS/BAS scale. Whereas, Carver and White identified the BIS as a unidimensional scale, they identified three separable BAS group factors - drive, fun seeking, and reward responsiveness -which Carver urged against combining into a BAS total score. Despite this, a BAS total score has been used extensively although researchers have yet to test whether a BAS general factor exists and, if so, whether a BAS total score can be interpreted as primarily being a measure of the general factor. The current study observed that the best fitting BAS factor model of those we tested was a hierarchical model with three group facets and a general factor. This model was largely invariant across both sex and race/ethnicity. We show, for the first time, that a general factor accounts for the majority of the variance in BAS total scores. Due to the superior fit of the hierarchical model and variance accounted for by the general factor, we conclude that researchers are psychometrically justified in using a BAS total score.     

Self‐esteem Is Mostly Stable Across Young Adulthood: Evidence from Latent STARTS Models

How stable is self‐esteem? This long‐standing debate has led to different conclusions across different areas of psychology. Longitudinal data and up‐to‐date statistical models have recently indicated that self‐esteem has stable and autoregressive trait‐like components and state‐like components. We applied latent STARTS models with the goal of replicating previous findings in a longitudinal sample of young adults (N = 4,532; M_age = 19.60, SD = 0.85; 55% female). In addition, we applied multigroup models to extend previous findings on different patterns of stability for men versus women and for people with high versus low levels of depressive symptoms. We found evidence for the general pattern of a major proportion of stable and autoregressive trait variance and a smaller yet substantial amount of state variance in self‐esteem across 10 years. Furthermore, multigroup models suggested substantial differences in the variance components: Females showed more state variability than males. Individuals with higher levels of depressive symptoms showed more state and less autoregressive trait variance in self‐esteem. Results are discussed with respect to the ongoing trait–state debate and possible implications of the group differences that we found in the stability of self‐esteem.     

Orthogonal higher order structure of the Wechsler Intelligence Scale For Children--fourth edition

According to J. B. Carroll's (1993) 3-stratum theory, performance on any subtest reflects a mixture of both 2nd-order and 1st-order factors. To disentangle these influences, variance explained by the general factor should be extracted first. The 1st-order factors are then residualized, leaving them orthogonal to the general factor and each other. When these methods were applied to the WISC-IV standardization sample, the general factor accounted for the greatest amount of common (71.3%) and total (38.3%) variance. The largest contribution by a first-order factor was 6.5% of total variance. It was recommended that interpretation of the WISC-IV not discount the strong general factor.     

Factor structure of the SCL-90-R: is there one?

A review of the literature on the factor structure of the Symptom Check List-90-R (SCL-90-R) and its precursors makes evident the many problems inherent in this clinical assessment tool as a measure of independent dimensions of symptom distress, particularly in psychiatric patients. The many versions of the Symptom Check List are evaluated on several criteria (e.g., factor stability, factor loadings, proportion of variance, etc.). It is concluded that interpreting nine dimensions for clinical purposes is highly questionable. It is perhaps still a better measure of general distress as was intended in its original version approximately three decades ago.     

Factor analysis and physical types

Physical measurements, obtained from several different age-groups and national groups, have been correlated and factorized. The largest of the investigations was based on 2,400 British airmen in the R.A.F., and the most recent included as many as 17 traits. The methods of factorization employed were those worked out in early investigations of mental and scholastic tests, and differed in minor respects from those more recently used by Thurstone in his re-analysis of some of our data. The factor patterns reveal a remarkable constancy from age to age and from one national group to another. The general factor accounts for about the same proportion of the variance as the general factor in cognitive tests. The largest of the bipolar factors classifies traits into longitudinal and transverse, thus in some measure confirming the traditional classification of body-types.     

Choice in transition: Replication and extension to preschool children in a naturalistic setting

This study replicated previous basic research into the dynamics of choice and extended this analysis to children's behavior in a naturalistic setting. Two preschoolers with disabilities were observed interacting with their teachers at baseline and during an experimental analysis involving four pairs of concurrent variable‐interval schedules of adult attention implemented by an experimenter. Each child was exposed to four experimental phases in which the relative reinforcer rates for on‐ and off‐task behavior were 10:1, 1:1, 1:10, and reversed back to 10:1. The 10:1 phase was designed to mimic the same schedules and types of adult attention observed at baseline. We used the generalized matching equation to model steady‐state behavior at the end of the transition phases and to evaluate changes in sensitivity at various points throughout the phases. Choice in transition was evaluated by plotting log behavior ratios by session, cumulated time on‐ and off‐task and cumulated attention for on‐ and off‐task behavior by session, and interreinforcer behavior ratios following different sequences of the first four reinforcer deliveries. The generalized matching equation accounted for a large proportion of variance in steady‐state responding, sensitivity values increased steadily throughout the phases, patterns of choice in transition were similar to those reported in basic research, and interreinforcer preference generally shifted toward the just‐reinforced alternative. These findings are consistent with previous basic research and support the generality of the dynamics of choice to children's on‐ and off‐task behavior reinforced by adult attention.     

Specific versus general skills and abilities: A job level examination of relationships with wage

The extensive literature purporting an upgrading in occupational skill requirements paired with the perception of a skill shortage in the workforce calls for the need to develop workplace skills and abilities. However, decisions about which skills to develop would be aided by information about which skills/abilities are valued most highly and lead to higher wage jobs. The job evaluation literature and labour‐market wage theory present competing hypotheses about skill—wage relationships. The ACT Inc.'s Work Keys® system, the prototype Occupational Information Network, and the fourth edition Dictionary of Occupational Titles job analytic databases were paired with concurrent wage data. These data made it possible to conduct a job‐level evaluation of whether specific skills/abilities could be identified that were most strongly linked to wage or whether broad skill/ability factors accounted for a majority of wage variance. Results indicated that a majority of the wage variance explainable by skills/abilities could be attributed to a general cognitive factor.     

CFA Models with a General Factor and Multiple Sets of Secondary Factors

We propose a class of confirmatory factor analysis models that include multiple sets of secondary or specific factors and a general factor. The general factor accounts for the common variance among manifest variables, whereas multiple sets of secondary factors account for the remaining source-specific dependency among subsets of manifest variables. A special case of the model is further proposed which constrains the specific factor loadings to be proportional to the general factor loadings. This proportional model substantially reduces the number of model parameters while preserving the essential structure of the general model. Furthermore, the proportional model allows for the interpretation of latent variables as the expected values of the observed manifest variables, decomposition of the variances, and the inclusion of interactions, similar to generalizability theory. We provide two applications to illustrate the utility of the proposed class of models.