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To estimate the parameters in a quantal response model, various alternative procedures have been used. A comparison is made between maximum likelihood, minimum chi-squared and modified minimum chi-squared in terms of first-order bias of parameter estimates, with particular reference to the standard probit model. It is shown that, in this respect, the procedures may differ widely, with maximum likelihood seeming the most satisfactory of the three alternatives.

量化响应模型中参数估计的偏差与准确性AI 解读

For a quantal response situation involving a total of n subjects, expressions are derived for biases correct to order n−1 and covariances correct to order n−2. These are applied to the standard probit model and it is shown that in this situation, first order biases can be appreciable, even for moderate n, and that the usual asymptotic results for variances can be considerably in error.

二元反应模型参数估计的偏差与准确性AI 解读

For a quantal response situation involving a total of n subjects, expressions are derived for biases correct to order n−1 and covariances correct to order n−2. These are applied to the standard probit model and it is shown that in this situation, first order biases can be appreciable, even for moderate n, and that the usual asymptotic results for variances can be considerably in error.