ARTICLE
ABSTRACT
This paper presents the critical overview of the statistical models that could be used in the social stress analysis. Such analysis is considered to consist of the identification of the social stressors, and of the measurement of their potency to destroy the social harmony. Four main groups of methods are discussed: item response models, factorial models, latent classification, and paired comparison.
REFERENCES
ANDERSEN E.B. (1980): Discrete Statistical Models with Social Science Applications, North-Holland, Amsterdam.
ANDERSEN E.B., Latent trait models , Journal of econometrics, 22, 1983, 215–227
ANDERSEN E.B., Comparing latent distributions, Psychometrika, 45, 1980, 121–134
ANDERSEN E.B., MADSEN M., Estimating the parameters of the latent population distribution, Psychometrika 42, 1977, 357–374
ANDRICH D., Rasch models for measurement, SAGE University Paper, 1988
BARTHOLOMEW D.J., KNOTT M., Latent variable models and factor analysis, ARNOLD, London, 1999
BOCK R.D., AITKIN M. (1981): Marginal maximum likelihood estimation of item parameters: application of an EM algorithm, Psychometrika 46, pp. 443–459
BOCK R.D., LIEBERMAN M.(1970): Fitting a response model for n dichotomously scored items, Psychometrika 435(2), pp. 179–197.
BRUNK H. D. (1960), Mathematical models for ranking from paired comparisons, American Statistical Association Journal, 9, 503–21
CHRISTOFFERSON A. (1975): Factor analysis of dichotomised variables, Psychometrika 40(1), pp. 5–31.
DAVID H.A., The method of paired comparisons, Griffin, London, 1969
EVERITT B.S.(1984): An introduction to latent variable models, Chapman& Hall, London.
EVERITT B.S., HAND D.J.(1981): Finite mixture distributions, Chapman& Hall, London.
FISCHER G.H., MOLENAAR I.W. eds (1995): Rasch models: foundations, recent developments and applications, Springer-Verlag, New York.
HAMBLETON R.K, SWAMINATHAN H., ROGERS H.J. (1991): Fundamentals of itemresponse theory, Sage Publications, Newbury Park, CA.
HOLLAND P.W. (1981): When are item response models consistent with observe data?, Psychometrika 46, pp. 79–92.
HOLLAND P.W. (1990): On the sampling theory foundations of item response theory models, Psychometrika 55, pp. 577–601.
HOLLAND P.W., ROSENBAUM P.R. (1986): Conditional association and unidimensionality in monotone latent variable models, Annals of Statistics, vol. 14, pp. 1523–1543
JUNKER B.W. (1993): Conditional association, essential independence and monotone unidimensional item response models, Annals of Statistics 21, pp. 1359–1378.
JUNKER B.W., ELLIS J.L. (1997): A characterization of monotone unidimensional latent variable models, Annals of Statistics 25, pp. 1327– 1343.
JUNKER B.W., SIJTSMA K., Nonparametric Item Response Theory in action, Applied Psychological Measurement,25, 2001, 211–220
KRAUTH J., Testkonstruktion und Testtheorie, BELTZ, 1995
LAZARSFELD P.F., HENRY N.W. (1968): Latent structure Analysis, Houghton-Mifflin, New York.
MOKKEN R.J. (1997): Nonparametric models for dichotomous responses, in W. van der Linden and R.K. Hambleton, eds, Handbook of Modern Item Response Theory, Springer-Verlag, New York pp. 351–367.
MOSTELLER F. (1951), Remarks on the method of paired comparisons, I, Psychometrika 16, pp. 3–9
NOETHER G., (1960), Remarks about a paired comparison model, Psychometrika 25, pp. 357–367
RASCH G. (1960): Probabilistic models for some intelligence and attainment tests, Poedagogiske Institut, Copenhagen.
28. ROSENBAUM P. R.(1984), Testing the conditional independence and monotonicity assumptions of item response theory, Psychometrika , 49, 425– 435.
STOUT W. (1987): A nonparametric approach for assessing latent trait unidimensionality, Psychometrika 52, pp. 589–617.
STOUT W. (1990): A new item response theory modelling approach with applications to unidimensionality assessment and ability estimation, Psychometrika 55, pp. 293–325.
