An Improvement on Estimation for Causal Models of Categorical Variables of Abilities and Task Performance

  • Kim, Sung-Ho (The author wishes to acknowledge the financial support of the Koren Research Foundation made in the program year of 1998)
  • Published : 2000.04.01

Abstract

The estimates from an EM when it is applied to a large causal model of 10 or more categorical variables are often subject to the initial values for the estimates. This phenomenon becomes more serious as the model structure becomes more serious as the model structure becomes more complicated involving more variables. In this regard Wu(1983) recommends among others that EMs are implemented several times with different sets of initial values to obtain more appropriate estimates. in this paper a new approach for initial values is proposed. The main idea is that we use initials that are calibrated to data. A simulation result strongly indicates that the calibrated initials give rise to the estimates that are far closer to the true values than the initials that are not calibrated.

Keywords

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