Studying group and time invariance in maximal reliability for multiple‐component measuring instruments via covariance structure modelling

A method for examining invariance in maximal reliability for weighted combinations of congeneric measures is described. The approach is developed within the framework of covariance structure modelling and allows one to ascertain whether a multi‐component instrument consisting of homogeneous measures is associated with the same minimal relative error variance in distinct populations or over time. The procedure yields as a by‐product an interval measure of discrepancy in maximal reliability across independent groups or assessment occasions, and is illustrated with two examples.     

Estimation of maximal reliability: A note on a covariance structure modelling approach

A one‐step covariance structure analysis procedure for estimation of maximal reliability of linear composites with congeneric measures is outlined. The approach is readily employed within a single modelling session using popular covariance structure analysis software, and permits simultaneous estimation of the optimal measure weights with standard errors. The method is illustrated by a numerical example.     

Incorporating prior theory in covariance structure analysis: A bayesian approach

A Bayesian approach to the testing of competing covariance structures is developed. The method provides approximate posterior probablities for each model under consideration without prior specification of individual parameter distributions. The method is based on ayesian updating using cross-validated pseudo-likelihoods. Given that the observed variables are the samefor all competing models, the approximate posterior probabilities may be obtained easily from the chi square values and other known constants, using only a hand calculator. The approach is illustrated using and example which illustrates how the prior probabilities can alter the results concerning which model specification is preferred.     

Alternative test criteria in covariance structure analysis: A unified approach

In the context of covariance structure analysis, a unified approach to the asymptotic theory of alternative test criteria for testing parametric restrictions is provided. The discussion develops within a general framework that distinguishes whether or not the fitting function is asymptotically optimal, and allows the null and alternative hypothesis to be only approximations of the true model. Also, the equivalent of the information matrix, and the asymptotic covariance matrix of the vector of summary statistics, are allowed to be singular. When the fitting function is not asymptotically optimal, test statistics which have asymptotically a chi-square distribution are developed as a natural generalization of more classical ones. Issues relevant for power analysis, and the asymptotic theory of a testing related statistic, are also investigated.This research has been supported by the U.S.-Spanish Joint Committee for Cultural and Educational Cooperation, grant number V-B.854020. The author wishes to express his gratitude to P. M. Bentler who provided very helpful suggestions and research facilities—with an stimulating working environment—at the University of California, Los Angeles, where this work was undertaken. Thanks are also due to W. E. Saris who provided very valuable comments to earlier versions of this paper. Finally, it has also to be acknowledged the editor's and reviewers suggestions which led to substantial improvements of this article.     

Bootstrap approach to inference and power analysis based on three test statistics for covariance structure models

We study several aspects of bootstrap inference for covariance structure models based on three test statistics, including Type I error, power and sample‐size determination. Specifically, we discuss conditions for a test statistic to achieve a more accurate level of Type I error, both in theory and in practice. Details on power analysis and sample‐size determination are given. For data sets with heavy tails, we propose applying a bootstrap methodology to a transformed sample by a downweighting procedure. One of the key conditions for safe bootstrap inference is generally satisfied by the transformed sample but may not be satisfied by the original sample with heavy tails. Several data sets illustrate that, by combining downweighting and bootstrapping, a researcher may find a nearly optimal procedure for evaluating various aspects of covariance structure models. A rule for handling non‐convergence problems in bootstrap replications is proposed.     

Response style analysis with threshold and multi‐process IRT models: A review and tutorial

Two different item response theory model frameworks have been proposed for the assessment and control of response styles in rating data. According to one framework, response styles can be assessed by analysing threshold parameters in Rasch models for ordinal data and in mixture‐distribution extensions of such models. A different framework is provided by multi‐process item response tree models, which can be used to disentangle response processes that are related to the substantive traits and response tendencies elicited by the response scale. In this tutorial, the two approaches are reviewed, illustrated with an empirical data set of the two‐dimensional ‘Personal Need for Structure’ construct, and compared in terms of multiple criteria. Mplus is used as a software framework for (mixed) polytomous Rasch models and item response tree models as well as for demonstrating how parsimonious model variants can be specified to test assumptions on the structure of response styles and attitude strength. Although both frameworks are shown to account for response styles, they differ on the quantitative criteria of model selection, practical aspects of model estimation, and conceptual issues of representing response styles as continuous and multidimensional sources of individual differences in psychological assessment.     

Examining change in maximal reliability for multiple‐component measuring instruments

A method for examining change in maximal reliability for pre‐specified sets of congeneric measures when developing a multi‐component instrument is outlined. The approach is applicable for purposes of estimation and testing of gain or loss in the maximal reliability coefficient as a consequence of adding or dropping one or more measures from a homogeneous composite with uncorrelated errors, as well as when one is concerned with optimal component choice for highest increase or correspondingly smallest drop in maximal reliability. The method is compared with a procedure for ascertaining change in unweighted sum score reliability, and implications for instrument construction and revision are discussed. The approach is illustrated with a numerical example.     

A parameter analysis method for the weight‐set to satisfy preference orders of alternatives in additive multi‐criteria value models

In the context of the additive multi‐criteria value model, this paper investigates how the set of criteria weights (weight‐set hereafter) can be determined according to the preference orders of alternatives given by the decision maker. A construction method is proposed for the weight‐set for different intervals of β, where β is a differential amount of value between the preference information on two alternatives. The results of this paper are important for sensitivity analysis in multi‐criteria decision making (MCDM) problems and multi‐criteria group decision analysis. Copyright © 2000 John Wiley & Sons, Ltd.     

The reliability of romantic love: A reliability generalization meta‐analysis

The present study is a reliability‐generalization meta‐analysis of 5 commonly used measures of romantic love: Rubin’s Loving and Liking scales, the Love Attitudes Scale, the Love Attitudes Scale–Short Form, the Passionate Love Scale, and the Triangular Love Scale. Data from 127 studies representing 38,132 participants provided internal consistency reliability estimates. The studies provide information on the average score reliability across studies and the effect of sample characteristics on score reliability across measures. The reliability of scores from several measures proved to be susceptible to the influence of sample characteristics, most notably, the ethnicity of the sample. The discussion provides recommendations to researchers and focuses on the ramifications of score reliability on love research.     

A component analysis of a parent‐conducted multi‐component treatment for food selectivity

Treatment packages including differential reinforcement of alternative (DRA) behavior and escape prevention in the form of a non‐removal of the spoon procedure have been shown to successfully increase food consumption. However, when these treatment components are introduced simultaneously, the treatment component(s) responsible for behavior change cannot be determined. The purpose of this study was to conduct a sequential component analysis of the following treatment components: Bite fading, manipulation of reinforcer magnitude, and escape prevention. For two participants, food consumption did not increase until after escape prevention was introduced. For one participant, increased food consumption was observed after the magnitude of reinforcement was increased; therefore, escape prevention was not necessary. Results were maintained at a 12‐week follow‐up for all participants. Copyright © 2010 John Wiley & Sons, Ltd.     

Confidence in work‐related goals and feelings of exhaustion during a therapeutic intervention for burnout: A time‐series approach

This study investigated recursive relations between confidence in achieving work‐related goals and work exhaustion among employees who participated in an intervention to reduce their burnout. Thirty‐six employees of age 33–59 years suffering from severe burnout (28 females and 8 males) filled in burnout and well‐being measures before and after a 10‐month therapeutic intervention. They also filled in weekly measures of confidence in work‐related goals (progress and capability) and work exhaustion throughout the intervention, as well as 4 weeks before and 4 weeks afterwards. Intra‐individual variation was modelled using dynamic factor analyses. The results showed that, for most participants, confidence in work‐related goals and work exhaustion during a given week could be predicted from those of the preceding week. Moreover, high self‐esteem predicted low weekly stability in goal confidence, whereas high burnout contributed to high weekly stability in work exhaustion. The intra‐individual stabilities in goal confidence and exhaustion also predicted which of the participants benefited from the intervention in terms of increasing well‐being and decreasing work‐related stress.     

Prioritizing emergency shelter areas using hybrid multi‐criteria decision approach: A case study

Every year, more than 400 natural disasters affect global population. Adopting a resilient approach strengthens communities to survive and recover well from destabilizing events. Disasters destroy or damage houses and infrastructure, which calls for arrangement of temporary establishments to provide immediate evacuation and shelter to affected population. These sites are vital for an effective relief and must be strategically planned. Communities living in disaster‐prone areas should prepare themselves well in advance for any future catastrophic event. This study adopts a hybrid group decision support approach for emergency shelter site selection problem. Initially, relevant factors for locating potential sites are identified by reviewing extant literature and through consultation from a panel of disaster management experts. Next, fuzzy analytic hierarchy process theory and technique for order preference by similarity to ideal solution have been used to prioritize identified criteria and to evaluate potential locations for displacement sites. A case study of the recent Nepal earthquake has been used to illustrate the effectiveness of the proposed model. The model offers a resilience building approach to prepare communities for any future contingency by proposing and prioritizing a set of planned displacement sites.     

Emotion regulation and psychopathological symptoms of Chinese school‐age children: A person‐centred and multi‐informant approach

Emotion regulation (ER) is a critical component of children's development. Many previous studies have utilised a single‐assessment method to reflect child ER, which might result in losing important information regarding the unique contribution of each informant. With a person‐centred approach and multi‐informant reports (mother, teacher and child), the current study examined 196 children's (age M = 9.21, SD = 1.10, range = 7–11 years; 51% girls) ER patterns and their associations with psychopathological symptoms in a Chinese sample. A model‐based clustering procedure resulted in 3 ER groups: the poor family ER group (n = 36), poor school ER group (n = 120), and overall good ER group (n = 40). Significant differences were found among ER clusters on teacher‐reported child psychopathological symptoms compared on the levels of withdrawn depression, somatic complain, thought problems and attention problems. No significant differences were found on the mother‐reported psychopathological symptoms. Compared with children in the poor school or poor family ER clusters, children in the overall good ER group demonstrated fewer psychopathological symptoms at school. Our results confirmed the advantage of adopting multi‐informant assessments to fully capture children's emotional profiles and linked these profiles with children's emotional and behavioural functioning at school.     

Improving an optimization‐based framework for sensitivity analysis in multi‐criteria decision‐making

The framework for sensitivity analysis in discrete multi‐criteria decision analysis developed by Rios Insua and French allows simultaneous variation of all parameters and applies to many paradigms for decision analysis. However, its computational load may inhibit use, particularly in the context of a decision conference where results are required in near real time. In order to improve on the current algorithm and its implementation, we investigate, on the one hand, an opportunistic approach aimed at reducing the number of optimization problems solved in the original framework and, on the other, an alternative framework based on distance analysis. Computational results on linear and bilinear models are reported. Copyright © 2001 John Wiley & Sons, Ltd.     

Triangulating consumers' perceptions of payment systems by using social representations theory: A multi‐method approach

Social systems play a pivotal role in shaping customers' views, the adoption process and subsequent product diffusion for novel products. Perceptions of Austrian consumers regarding payment systems were assessed in a cross‐sectional analysis applying social representations theory. Social representations help to unravel the sources of individuals' attitudinal or perceptual similarities and differences, which often stem from inter‐group differences. In short, they are useful for the investigation of ‘deeper structure’ aspects of consumer behaviour, as has been shown in previous studies. This may be seen as a further step forward for marketing research, which operates largely on social phenomena. This study addresses the shortage of non‐cognitive‐based research in marketing by offering a methodological approach that uses triangulation on the basis of associative answers from social groups. A four‐step analytic design revealed that consumer groups transpose the abstract concept of payment systems into tangible objects and processes in a similar way; however, their social background impacted which value was attached to established as well as new means of payment. Cash is still seen as the prototypical form of payment; newer forms, such as credit cards or ATM cards, appear already in the periphery of representations, urgently needing well‐concerted marketing efforts to become recognized as substitutes for cash. From a managerial view, the research employs social phenomena as a basis for segmenting natural rather than nominal groups in order to better serve consumers' needs in an increasingly connected social reality. Copyright © 2013 John Wiley & Sons, Ltd.     

A multi‐process model of self‐regulation: Influences of Mindfulness,Integrative Self‐Knowledge and Self‐Control in Iran

Self‐regulation presumably rests upon multiple processes that include an awareness of ongoing self‐experience, enduring self‐knowledge and self‐control. The present investigation tested this multi‐process model using the Five‐Facet Mindfulness Questionnaire (FFMQ) and the Integrative Self‐Knowledge and Brief Self‐Control Scales. Using a sample of 1162 Iranian university students, we confirmed the five‐factor structure of the FFMQ in Iran and documented its factorial invariance across males and females. Self‐regulatory variables correlated negatively with Perceived Stress, Depression, and Anxiety and positively with Self‐Esteem and Satisfaction with Life. Partial mediation effects confirmed that self‐regulatory measures ameliorated the disturbing effects of Perceived Stress. Integrative Self‐Knowledge and Self‐Control interacted to partially mediate the association of Perceived Stress with lower levels of Satisfaction with Life. Integrative Self‐Knowledge, alone or in interaction with Self‐Control, was the only self‐regulation variable to display the expected mediation of Perceived Stress associations with all other measures. Self‐Control failed to be implicated in self‐regulation only in the mediation of Anxiety. These data confirmed the need to further examine this multi‐process model of self‐regulation.     

Memory for targets in a multi‐level simulated‐environment: A comparison between able‐bodied and physically disabled children

Two groups of children, one able‐bodied and the other with physical disabilities, explored a symmetrical three‐tiered virtual building that contained six distinctive target objects, two on each storey. In a subsequent test, the target objects were removed and participants were asked to make judgments of the directions to the former target locations from each floor in turn. At each test site, judgments were required for targets that were formerly on the same floor and for those on higher and lower floors. Relative tilt error scores suggested a bias for both groups, in that targets that were higher than the test location were judged as consistently lower than their actual position, whereas targets that were lower than the test location were judged as higher than their actual position. Absolute tilt errors revealed an asymmetry in both groups, with more accurate tilt errors for judgments directed to lower than higher floors. The relevance of these results for the source of the asymmetry is discussed.     

Re‐Examining Machiavelli: A Three‐Dimensional Model of Machiavellianism in the Workplace

Machiavellianism has been studied extensively over the past 40 years as a personality characteristic that shares features with the manipulative leadership tactics Machiavelli advocated in The Prince. We introduce a new model of Machiavellianism based in organizational settings that is multidimensional, incorporating aspects not previously included in Machiavellianism scales. Our model consists of 3 factors: maintaining power, harsh management tactics, and manipulative behaviors. The results of 3 studies are summarized, discussing the development of these 3 factors and how they relate to individual‐difference and organizational variables.     

Personality and religious values among adolescents: A three‐wave longitudinal analysis

Using three waves of data, we assessed the relationships between endorsement of religious values, some of the major personality dimensions, and social and emotional well‐being amongst teenagers. Participants were 784 high school students at Time 1 (382 males and 394 females; 8 did not indicate their gender) and 563 provided data at each of Time 1, Time 2 and Time 3. We examined the impact of changes in (Eysenckian) psychoticism and conscientiousness from Time 1 to Time 2 on religious values assessed at Time 3. Both personality and personality change predicted religious values and the specific effects depended on gender. Participants higher in hope, joviality, psychological acceptance and mindfulness also tended to be higher in religious values. The implications of these results for adolescent well‐being and resilience are discussed.