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若干单变量 Bradley–Terry 模型的加权最小二乘分析AI 解读

The approach of Grizzle, Starmer, and Koch (1969) to analyzing categorical data using linear and loglinear transformations is applied to the analysis of univariate paired and triple comparison experiments. This method of analysis produces noniterative weighted least-squares estimates of the preference ratings corresponding to the treatments under test and allows for testing hypotheses relative to their values within the framework of the general linear hypothesis. Further,…

若干单变量 Bradley–Terry 模型的加权最小二乘分析AI 解读

The approach of Grizzle, Starmer, and Koch (1969) to analyzing categorical data using linear and loglinear transformations is applied to the analysis of univariate paired and triple comparison experiments. This method of analysis produces noniterative weighted least-squares estimates of the preference ratings corresponding to the treatments under test and allows for testing hypotheses relative to their values within the framework of the general linear hypothesis. Further,…

成对比较实验的局部渐近最严格检验AI 解读

Following the results of Bhat and Nagnur [2], the locally asymptotically most stringent test of the hypothesis of no preference in paired comparison experiments is derived for the models of Rao and Kupper [9] and Davidson [3]. It is shown that the asymptotic relative efficiency of these tests when compared to the test based on the likelihood ratio statistic is unity.

成对比较试验的局部渐近最严检验AI 解读

Following the results of Bhat and Nagnur [2], the locally asymptotically most stringent test of the hypothesis of no preference in paired comparison experiments is derived for the models of Rao and Kupper [9] and Davidson [3]. It is shown that the asymptotic relative efficiency of these tests when compared to the test based on the likelihood ratio statistic is unity.