Insufficient discriminant validity:a comment on Bove, Pervan, Beatty and Shiu (2009)

Bove, Pervan, Beatty, and Shiu [Bove, LL, Pervan, SJ, Beatty, SE, Shiu, E. Service worker role in encouraging customer organizational citizenship behaviors. J Bus Res 2009;62(7):698–705.] develop and test a latent variable model of the role of service workers in encouraging customers' organizational citizenship behaviors. However, Bove et al. [Bove, LL, Pervan, SJ, Beatty, SE, Shiu, E. Service worker role in encouraging customer organizational citizenship behaviors. J Bus Res 2009;62(7):698–705.] claim support for hypothesized relationships between constructs that, due to insufficient discriminant validity regarding certain constructs, may be inaccurate. This research comment discusses what discriminant validity represents, procedures for establishing discriminant validity, and presents an example of inaccurate discriminant validity assessment based upon the work of Bove et al. [Bove, LL, Pervan, SJ, Beatty, SE, Shiu, E. Service worker role in encouraging customer organizational citizenship behaviors. J Bus Res 2009;62(7):698–705.]. Solutions to discriminant validity problems and a five-step procedure for assessing discriminant validity then conclude the paper. This comment hopes to motivate a review of discriminant validity issues and offers assistance to future researchers conducting latent variable analysis.

Statnote 29:discriminant analysis

Discriminant analysis (also known as discriminant function analysis or multiple discriminant analysis) is a multivariate statistical method of testing the degree to which two or more populations may overlap with each other. It was devised independently by several statisticians including Fisher, Mahalanobis, and Hotelling ). The technique has several possible applications in Microbiology. First, in a clinical microbiological setting, if two different infectious diseases were defined by a number of clinical and pathological variables, it may be useful to decide which measurements were the most effective at distinguishing between the two diseases. Second, in an environmental microbiological setting, the technique could be used to study the relationships between different populations, e.g., to what extent do the properties of soils in which the bacterium Azotobacter is found differ from those in which it is absent? Third, the method can be used as a multivariate ‘t’ test , i.e., given a number of related measurements on two groups, the analysis can provide a single test of the hypothesis that the two populations have the same means for all the variables studied. This statnote describes one of the most popular applications of discriminant analysis in identifying the descriptive variables that can distinguish between two populations.

Factor analysis and discriminant validity:a brief review of some practical issues

Growth in availability and ability of modern statistical software has resulted in greater numbers of research techniques being applied across the marketing discipline. However, with such advances come concerns that techniques may be misinterpreted by researchers. This issue is critical since misinterpretation could cause erroneous findings. This paper investigates some assumptions regarding: 1) the assessment of discriminant validity; and 2) what confirmatory factor analysis accomplishes. Examples that address these points are presented, and some procedural remedies are suggested based upon the literature. This paper is, therefore, primarily concerned with the development of measurement theory and practice. If advances in theory development are not based upon sound methodological practice, we as researchers could be basing our work upon shaky foundations.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Incremental tensor biased discriminant analysis:a new color-based visual tracking method

Most existing color-based tracking algorithms utilize the statistical color information of the object as the tracking clues, without maintaining the spatial structure within a single chromatic image. Recently, the researches on the multilinear algebra provide the possibility to hold the spatial structural relationship in a representation of the image ensembles. In this paper, a third-order color tensor is constructed to represent the object to be tracked. Considering the influence of the environment changing on the tracking, the biased discriminant analysis (BDA) is extended to the tensor biased discriminant analysis (TBDA) for distinguishing the object from the background. At the same time, an incremental scheme for the TBDA is developed for the tensor biased discriminant subspace online learning, which can be used to adapt to the appearance variant of both the object and background. The experimental results show that the proposed method can track objects precisely undergoing large pose, scale and lighting changes, as well as partial occlusion. © 2009 Elsevier B.V.

Quantifying evidence for forensic authorship analysis

The judicial interest in ‘scientific’ evidence has driven recent work to quantify results for forensic linguistic authorship analysis. Through a methodological discussion and a worked example this paper examines the issues which complicate attempts to quantify results in work. The solution suggested to some of the difficulties is a sampling and testing strategy which helps to identify potentially useful, valid and reliable markers of authorship. An important feature of the sampling strategy is that these markers identified as being generally valid and reliable are retested for use in specific authorship analysis cases. The suggested approach for drawing quantified conclusions combines discriminant function analysis and Bayesian likelihood measures. The worked example starts with twenty comparison texts for each of three potential authors and then uses a progressively smaller comparison corpus, reducing to fifteen, ten, five and finally three texts per author. This worked example demonstrates how reducing the amount of data affects the way conclusions can be drawn. With greater numbers of reference texts quantified and safe attributions are shown to be possible, but as the number of reference texts reduces the analysis shows how the conclusion which should be reached is that no attribution can be made. The testing process at no point results in instances of a misattribution.

Rhythms of life:antecedents and outcomes of work-family balance among employed parents

This study examined antecedents and outcomes of a fourfold taxonomy of work-family balance in terms of the direction of influence (work-family vs. family-work) and type of effect (conflict vs. facilitation). Respondents were full-time employed parents in India. Confirmatory factor analysis results provided evidence for the discriminant validity of M. R. Frone's (2003) fourfold taxonomy of work-family balance. Results of moderated regression analysis revealed that different processes underlie the conflict and facilitation components. Furthermore, gender had only a limited moderating influence on the relationships between the antecedents and the components of work-family balance. Last, work-family facilitation was related to the work outcomes of job satisfaction and organizational commitment.

On the validity of subjective measures of company performance

Subjective measures of company performance are widely used in research and typically are interpreted as equivalent to objective measures. Yet, the assumption of equivalence is open to challenge. We compared the use of both types of measure in 3 separate samples. Findings were consistent in showing that: (a) subjective and objective measures of company performance were positively associated (convergent validity); (b) those relationships were stronger than those between measures of differing aspects of performance using the same method (discriminant validity); and (c) the relationships of subjective and objective company performance measures with a range of independent variables were equivalent (construct validity).

Validating the organizational climate measure:links to managerial practices, productivity and innovation

This paper describes the development and validation of a multidimensional measure of organizational climate, the Organizational Climate Measure (OCM), based upon Quinn and Rohrbaugh's Competing Values model. A sample of 6869 employees across 55 manufacturing organizations completed the questionnaire. The 17 scales contained within the measure had acceptable levels of reliability and were factorially distinct. Concurrent validity was measured by correlating employees' ratings with managers' and interviewers' descriptions of managerial practices and organizational characteristics. Predictive validity was established using measures of productivity and innovation. The OCM also discriminated effectively between organizations, demonstrating good discriminant validity. The measure offers researchers a relatively comprehensive and flexible approach to the assessment of organizational members' experience and promises applied and theoretical benefits. Copyright © 2005 John Wiley & Sons, Ltd.

Minority dissent and team innovation:the importance of participation in decision making

This study integrates research on minority dissent and individual creativity, as well as team diversity and the quality of group decision making, with research on team participation in decision making. From these lines of research, it was proposed that minority dissent would predict innovation in teams but only when teams have high levels of participation in decision making. This hypothesis was tested in 2 studies, 1 involving a homogeneous sample of self-managed teams and 1 involving a heterogeneous sample of cross-functional teams. Study 1 suggested that a newly developed scale to measure minority dissent has discriminant validity. Both Study 1 and Study 2 showed more innovations under high rather than low levels of minority dissent but only when there was a high degree of participation in team decision making. It is concluded that minority dissent stimulates creativity and divergent thought, which, through participation, manifest as innovation.

Individual spirit at work and its relationship with employee work attitudes and organisational outcomes:An empirical examination in corporate Thailand

The purpose of this thesis is to conduct empirical research in corporate Thailand in order to (1) validate the Spirit at Work Scale (2) investigate the relationships between individual spirit at work and three employee work attitudinal variables (job satisfaction, organisational identification and psychological well-being) and three organisational outcomes (in-role performance, organisational citizenship behaviours (OCB), and turnover intentions) (3) further examine causal relations among these organisational behaviour variables with a longitudinal design (4) examine three employee work attitudes as mediator variables between individual spirit at work and three organisational outcomes and (5) explore the potential antecedents of organisational conditions that foster employee experienced individual spirit at work. The two pilot studies with 155 UK and 175, 715 Thai samples were conducted for validation testing of the main measure used in this study: Spirit at Work Scale (Kinjerski & Skrypnek, 2006a). The results of the two studies including discriminant validity analyses strongly provided supportive evidence that Spirit at Work Scale (SAWS) is a sound psychometric measure and also a distinct construct from the three work attitude constructs. The final model of SAWS contains a total of twelve items; a three factor structure (meaning in work, sense of community, and spiritual connection) in which the sub-factors loaded on higher order factors and also had very acceptable reliability. In line with these results it was decided to use the second-order of SAWS model for Thai samples in the main study and subsequent analysis. The 715 completed questionnaires were received from the first wave of data collection during July - August 2008 and the second wave was conducted again within the same organisations and 501 completed questionnaires were received during March - April 2009. Data were obtained through 49 organisations which were from three types of organisations within Thailand: public organisations, for-profit organisations, and notfor-profit organisations. Confirmatory factor analysis of all measures used in the study and hypothesised model were tested with structural equation modelling techniques. The results were greatly supportive for the direct structural model and partially supportive for the fully mediated model. Moreover, there were different findings across self report and supervisor rating on performance and OCB models. Additionally, the antecedent conditions that fostered employees experienced individual spirit at work and the implications of these findings for research and practice are discussed.

The development of a short scale measuring aggressiveness and anger in competitive athletes

Objectives: The study of aggression and anger in competitive sport relies on accurate and economical measurement via observation, interview and questionnaire. Unfortunately, extant questionnaires have been criticised for having poor validity, are not sport specific, or reflect mood states rather than trait qualities. Therefore, a measure of trait anger and aggressiveness in competitive athletes was developed. Method: A list of statements representing aggressiveness and anger was generated and distributed to competitive athletes from diverse sports. Exploratory and confirmatory analyses were used to verify the theoretically predicted factor structure. Correlations with an extant measure of aggression and anger were used to ascertain concurrent validity. Discriminant validity was tested by comparing males with females, and aggressive with non-aggressive footballers. Results: A 12-item scale (Competitive Aggressiveness and Anger Scale, CAAS) consisting of two subscales was derived using principal component factor analysis with oblimin rotation. Confirmatory factor analysis using structural equation modelling confirmed the overall structure. Test-retest correlation, construct and discriminant validities were good, supporting the utility of the scale as a measure of athlete trait aggressiveness and anger. Conclusions: The CAAS appears to be a useful measure of athletic anger and aggressiveness. Its brevity and ability to discriminate aggressive from non-aggressive athletes should prove useful for future research concerning aggressive behaviour in competitive athletes. © 2006 Elsevier Ltd. All rights reserved.

A study of cluster analysis techniques and their applications

This thesis seeks to describe the development of an inexpensive and efficient clustering technique for multivariate data analysis. The technique starts from a multivariate data matrix and ends with graphical representation of the data and pattern recognition discriminant function. The technique also results in distances frequency distribution that might be useful in detecting clustering in the data or for the estimation of parameters useful in the discrimination between the different populations in the data. The technique can also be used in feature selection. The technique is essentially for the discovery of data structure by revealing the component parts of the data. lhe thesis offers three distinct contributions for cluster analysis and pattern recognition techniques. The first contribution is the introduction of transformation function in the technique of nonlinear mapping. The second contribution is the us~ of distances frequency distribution instead of distances time-sequence in nonlinear mapping, The third contribution is the formulation of a new generalised and normalised error function together with its optimal step size formula for gradient method minimisation. The thesis consists of five chapters. The first chapter is the introduction. The second chapter describes multidimensional scaling as an origin of nonlinear mapping technique. The third chapter describes the first developing step in the technique of nonlinear mapping that is the introduction of "transformation function". The fourth chapter describes the second developing step of the nonlinear mapping technique. This is the use of distances frequency distribution instead of distances time-sequence. The chapter also includes the new generalised and normalised error function formulation. Finally, the fifth chapter, the conclusion, evaluates all developments and proposes a new program. for cluster analysis and pattern recognition by integrating all the new features.

Exploratory database visualisation: the application and assessment of data and dimensionality reduction

This thesis describes the development of a complete data visualisation system for large tabular databases, such as those commonly found in a business environment. A state-of-the-art 'cyberspace cell' data visualisation technique was investigated and a powerful visualisation system using it was implemented. Although allowing databases to be explored and conclusions drawn, it had several drawbacks, the majority of which were due to the three-dimensional nature of the visualisation. A novel two-dimensional generic visualisation system, known as MADEN, was then developed and implemented, based upon a 2-D matrix of 'density plots'. MADEN allows an entire high-dimensional database to be visualised in one window, while permitting close analysis in 'enlargement' windows. Selections of records can be made and examined, and dependencies between fields can be investigated in detail. MADEN was used as a tool for investigating and assessing many data processing algorithms, firstly data-reducing (clustering) methods, then dimensionality-reducing techniques. These included a new 'directed' form of principal components analysis, several novel applications of artificial neural networks, and discriminant analysis techniques which illustrated how groups within a database can be separated. To illustrate the power of the system, MADEN was used to explore customer databases from two financial institutions, resulting in a number of discoveries which would be of interest to a marketing manager. Finally, the database of results from the 1992 UK Research Assessment Exercise was analysed. Using MADEN allowed both universities and disciplines to be graphically compared, and supplied some startling revelations, including empirical evidence of the 'Oxbridge factor'.