Advertisement

Psychometrika

, Volume 24, Issue 4, pp 283–302 | Cite as

An approach to mental test theory

  • Frederic M. Lord
Article

Keywords

Public Policy Statistical Theory Test Theory Mental Test 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Barton D. E. and Dennis, K. E. The conditions under which Gram-Charlier and Edgeworth curves are positive definite and unimodal.Biometrics, 1952,39, 425–426.Google Scholar
  2. [2]
    Basmann, R. L. The computation of generalized classical estimates of coefficients in a structural equation.Econometrica, 1959,27, 72–81.Google Scholar
  3. [3]
    Buckingham, R. A.Numerical methods. London: Pitman, 1957.Google Scholar
  4. [4]
    Collatz, L.Numerische Behandlung von Differential-Gleichungen. Berlin: Springer, 1951.Google Scholar
  5. [5]
    Crout, P. D. An application of polynomial approximation to the solution of integral equations arising in physical problems.J. math. Phys., 1940,19, 34–92.Google Scholar
  6. [6]
    Cureton, E. E. and Tukey, J. W. Smoothing frequency distributions, equating tests, and preparing norms.Amer. Psychologist, 1951,6, 404. (Abstract)Google Scholar
  7. [7]
    Ferguson, T. On the existence of linear regression in linear structural relations.Univ. Calif. Publications in Statistics, 1955,2, No. 7.Google Scholar
  8. [8]
    Gaffey, W. R. A consistent estimator of a component of a convolution.Ann. math. Statist., 1959,30, 198–205.Google Scholar
  9. [9]
    Geary, R. C. Inherent relations between random variables.Proc. Roy. Irish Acad., 1942,47, 63–76.Google Scholar
  10. [10]
    Geary, R. C. Determination of linear relations between systematic parts of variables with errors of observation the variances of which are unknown.Econometrica, 1949,17, 30–58.Google Scholar
  11. [11]
    Geary, R. C. Relations between statistics: The general and the sampling problem when the samples are large.Proc. Roy. Irish Acad., 1943,49, 177–196.Google Scholar
  12. [12]
    Johnson, N. L. and Rogers, C. A. The moment problem for unimodal distributions.Ann. math. Statist., 1951,22, 433–439.Google Scholar
  13. [13]
    Kendall, M. G.The advanced theory of statistics. London: Griffin, 1948.Google Scholar
  14. [14]
    Kendall, M. G. Regression, linear structure, and functional relationship.Biometrika, 1951,38, 11–25.Google Scholar
  15. [15]
    Koopmans, T. C. and Reiersøl, O. The identification of structural characteristics.Ann. math. Statist., 1950,21, 165–181.Google Scholar
  16. [16]
    Lord, F. M. Statistical inferences about true scores.Psychometrika, 1959,24, 1–17.Google Scholar
  17. [17]
    Lord, F. M. Use of true-score theory to predict moments of univariate and bivariate observed-score distributions. Princeton: Educ. Test. Serv. Res. Bull. 59-6, 1959.Google Scholar
  18. [18]
    Lord, F. M. An empirical study of the normality and independence of errors of measurement in test scores.Psychometrika, in press.Google Scholar
  19. [19]
    Lord, F. M. Inferences about true scores from parallel test forms.Educ. psychol. Measmt, 1959,19, 331–336.Google Scholar
  20. [20]
    Lord, F. M. The joint cumulants of true values and errors of measurement.Ann. math. Statist., in press.Google Scholar
  21. [21]
    Madansky, A. The fitting of straight lines when both variables are subject to error.J. Amer. statist. Ass., 1959,54, 173–205.Google Scholar
  22. [22]
    Mallows, C. L. Note on the moment-problem for unimodal distributions when one or both terminals are known.Biometrics, 1956,43, 224–227.Google Scholar
  23. [23]
    Moran, P. A. P. A significance test for an unidentifiable relation.J. Roy. statist. Soc. B, 1956,18, 61–64.Google Scholar
  24. [24]
    Neyman, J. and Scott, E. L. Consistent estimates based on partially consistent observations.Econometrica, 1948,16, 1–32.Google Scholar
  25. [25]
    Pollard, H. Distribution functions containing a Gaussian factor.Proc. Amer. math. Soc., 1953,4, 578–582.Google Scholar
  26. [26]
    Reiersøl, O. Identifiability of a linear relation between variables which are subject to error.Econometrica, 1950,18, 375–389.Google Scholar
  27. [27]
    Robbins, H. An empirical Bayes approach to statistics. In J. Neyman (Ed.),Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability. Vol. 1. Berkeley: Univ. California Press, 1956. Pp. 157–163.Google Scholar
  28. [28]
    Royden, H. L. Bounds on a distribution function when its firstn moments are given.Ann. math. Statist., 1953,24, 361–376.Google Scholar
  29. [29]
    Standish, C.N-dimensional distributions containing a normal component.Ann. math. Statist., 1956,27, 1161–1165.Google Scholar
  30. [30]
    Steinhaus, H. The problem of estimation.Ann. math. Statist., 1957,28, 633–648.Google Scholar
  31. [31]
    Tricomi, F. G.Integral equations. New York: Interscience, 1957.Google Scholar
  32. [32]
    Trumpler, R. J. and Weaver, H. F.Statistical astronomy. Berkeley: Univ. California Press, 1953.Google Scholar
  33. [33]
    Tukey, J. W. Components in regression.Biometrics, 1951,7, 33–69.Google Scholar
  34. [34]
    Wallace, D. L. Asymptotic approximations to distributions.Ann. math. Statist. 1958,29, 635–654.Google Scholar
  35. [35]
    Wolfowitz, J. Estimation of the components of stochastic structures.Proc. Nat. Acad. Sci., 1954,40, 602–606.Google Scholar
  36. [36]
    Williams, E. J. Significance tests for discriminant functions and linear functional relationships.Biometrics, 1955,42, 360–381.Google Scholar
  37. [37]
    Zelen, M. Bounds on a distribution function that are functions ofμ 0 toμ 4.J. Res. Nat. Bur. Standards, 1954,53, No. 6, paper 2556.Google Scholar

Copyright information

© Psychometric Society 1959

Authors and Affiliations

  • Frederic M. Lord
    • 1
  1. 1.Educational Testing ServiceUSA

Personalised recommendations