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Psychometrika

, Volume 27, Issue 2, pp 183–192 | Cite as

A comparison of three methods of fitting the normal ogive

  • Elliot M. Cramer
Article

Abstract

The Mueller-Urban method of fitting the normal ogive is derived, and the inadequacies of its inherent assumptions are discussed. This and the unweighted least squares method are compared to the maximum likelihood solution which is shown to be very close to the “ideal” least squares solution. As an empirical demonstration of the superiority of the maximum likelihood solution, random ogives are fitted by all three methods and they are compared on the basis of the expected values and the standard errors of the estimates. It is concluded that the maximum likelihood solution is uniformly superior to the others in all respects.

Keywords

Standard Error Public Policy Statistical Theory Empirical Demonstration Inherent Assumption 
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.

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Copyright information

© Psychometric Society 1962

Authors and Affiliations

  • Elliot M. Cramer
    • 1
  1. 1.The Johns Hopkins UniversityUSA

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