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负二项变异下计数数据的单因素组间分析AI 解读

Two C(α) statistics (Neyman, 1959) for testing the equality of the means of several groups of count data in the presence of a common dispersion parameter are derived. The performance of the two C(α) statistics, the likelihood ratio statistic and two more statistics based on transformed data (Anscombe, 1948) is then compared in terms of size and power by using Monte Carlo simulations. The C(α) statistics are recommended. The C(α) statistics for testing the equality of the…

具有负二项变异的计数数据单因素分析AI 解读

Two C(α) statistics (Neyman, 1959) for testing the equality of the means of several groups of count data in the presence of a common dispersion parameter are derived. The performance of the two C(α) statistics, the likelihood ratio statistic and two more statistics based on transformed data (Anscombe, 1948) is then compared in terms of size and power by using Monte Carlo simulations. The C(α) statistics are recommended. The C(α) statistics for testing the equality of the…