A Model for Institutional Disturbances

Zeeman, E. C.; Hall, C. Scott; Harrison, Patrick; Marriage, G. H.; Shapland, P. H.

doi:10.1111/j.2044-8317.1976.tb00703.x

Cited by 55 publications

(17 citation statements)

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“…After the theoretical model is worked out, however, it is necessary to test it empirically. Different experimental models have been used or suggested for different purposes, including graphic analysis only (Zeeman, Hall, Harrison, Marriage, & Shapland, 1976), behavior surface to control surface mapping rules (Benham & Kozak, 1976;Gilmore, 1981;Guastello, 1981a;Jiobu & Lundgren, 1978;Oliva, Peters, & Murthy, 1981;Sheridan, 1980;Smith, 1980), qualitative classification of time series patterns (Guastello, 1981b), stationary regression models (Cobb, 1978(Cobb, , 1981a(Cobb, , 1981b. The latter group is of particular interest since it is the closest to what will be discussed.…”

Section: Catastrophe Theorymentioning

confidence: 99%

Moderator regression and the cusp catastrophe: Application of two-stage personnel selection, training, therapy, and policy evaluation

Guastello

1982

Syst. Res.

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This article demonstrates the applicability of the cusp catastrophe model to a twostage validity study for personnel selection which can simultaneously assess the success of a training program. Personnel selection is of interest substantively since its literature spans psychology, education, economics, management science, political philosophy, statistics, and psychometric theory. The basic problem is, in turn, pertinent to the study of any individuals integrating into an organization, or a therapy or social program.In an empirical example regression coefficients for conventional and cusp-difference models were compared using partially real and partially simulated data. Subjects were 272 salespersons from a Midwestern firm, of which 17 were Spanish-speaking Americans. Group membership was the dummy coded bifurcation (moderator) factor. A composite of personality and ability test scores was the asymmetry factor. The cusp model was a more efficient predictor of performance (R" = .39) than the moderator model (R' = .04) or a control equation using a bimodal transformation (R" = .04). It was also possible to obtain implicit discriminant functions (IDFS) to predict the top performing 16% of the sample (R' = .71), and the low performing 16% (R" = 35). The results were interpreted as supporting the usefulness of the statistical catastrophe models for twostage personnel selection and training, and similar problems. Differential impact, moderator, and interaction effects in organizational literature were discussed vis-a-vis the bifurcation concept.

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Section: Catastrophe Theorymentioning

confidence: 99%

Moderator regression and the cusp catastrophe: Application of two-stage personnel selection, training, therapy, and policy evaluation

Guastello

1982

Syst. Res.

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“…The prison riot study (Zeeman, Hall, Harrison, Marriage, & Shapland, 1976) has a more fundamental problem. The obtained results showed disturbances occurring in a pattern that did not conform to the expectations of the cusp model, and the authors attempted to remedy the situation by suggesting that two cusp patterns ought to be imposed.…”

Section: Applied Catastrophe Theorymentioning

confidence: 99%

Catastrophe modeling of equity in organizations

Guastello

1981

Syst. Res.

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Catastrophe theory is a general systems theory for predicting di~~ontinuous change by one of seven elementary topological models. Catastrophe models have been applied to changes involving living and nonliving systems, addressing problems in physics, biology, economics, psychology, and other disciplines. The majority of quantitative successes has occurred with problems involving "hard" data; social modeling, and its inherent data problems, has not been 80 successful.In this paper principles of signal detection theory are applied to three elementary models in order to develop a butterfiy model of equity and productivity in industry. In the model four sources of information (control dimensions) are processed by the subject, with a dependent spectrum of behavior resulting. The model has implications at the individual and org&&ional levels. The signal detection approach involves a conversion from absolute to normative scaling. At the lowest dimension levels catastrophe and regression-produced surfaces are the same. At higher dimensional levels, discrepancies between the two types of surfaces become evident. The paper explores the assumptions underlying the two systems and the need for translational methodology. Criticisms addressed to social appficatiOnS of catastrophe theory by Sussman and Zahler (1978) are also considered, along with criticisms of social science theory in general.

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“…The topological nature of the models implies that they are basically free from dependence on the metrics used for measurement (Jiobu & Lundgren, 1978). Hence averaging or some similar approach has been used to estimate variable values (see Zeeman et al, 1976;Oliva, Peters & Murthy, 1981).…”

Section: Deterministic Modelsmentioning

confidence: 99%

“…Initially, a graphical approach was presented by Zeeman et al (1976) to model prison disturbances. Most would agree that the approach was less than satisfactory (Sussman & Zahler, 1978a,b;Jiobu & Lundgren, 1978).…”

Section: Summary Of Key Empirical Issuesmentioning

confidence: 99%

“…As a result, catastrophe theory was dismissed by the majority of researchers as a serious approach to modeling. Slowly, catastrophe theory has recently become more popular as the number and quality of methodologies for empirically testing catastrophe models have increased (e.g., Zeeman et al, 1976;Benhem & Kozak, 1976;Jiobu & Lundgren, 1978;Cobb, 1978Cobb, ,1981Cobb, , 1983Sheridan & Ableson, 1983;Guastello, 1982a;Stewart & Peregoy, 1983;Anderson, 1985;and Cobb & Zacks, 1985), and applications of the theory are being subjected to more rigorous testing (e.g., Oliva, Peters & Murthy, 1981;Sheridan & Abelson, 1983;Guastello, 1985a and1985b;Anderson, 1985). Work by Cobb (e.g., 1978Cobb (e.g., ,1981 has laid the groundwork for various statistical estimation methods.…”

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confidence: 98%

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Gemcat: A general multivariate methodology for estimating catastrophe models

et al. 1987

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This paper presents a methodology for empirically estimating any specified univariate or multivariate catastrophe theory model. As such, the paper is appropriate for those interested in modeling virtually all levels of living systems and subsystems which can be described by catastrophe theory models, as well as those interested in testing cross-level hypotheses about such systems and subsystems. The lack of such flexible estimation procedures has limited the potential application of catastrophe modeling in the social and behavioral sciences. More specifically, a methodology called GEMCAT is presented, using the cusp model for expositional convenience, which allows the traditional canonical catastrophe model variables to be described as latent constructs of univariate or multivariate observable variable sets. A Monte Car10 analysis is presented demonstrating the performance of the methodology under various conditions. Furthermore, it is shown how this method is superior to the common practice of generating univariate composites (e.g., by summing, averaging, etc.) which has been traditionally used because of either computational convenience or the lack of such a methodology.

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A Model for Institutional Disturbances

Cited by 55 publications

References 1 publication

Moderator regression and the cusp catastrophe: Application of two-stage personnel selection, training, therapy, and policy evaluation

Moderator regression and the cusp catastrophe: Application of two-stage personnel selection, training, therapy, and policy evaluation

Catastrophe modeling of equity in organizations

Gemcat: A general multivariate methodology for estimating catastrophe models

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