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双侧数据均有缺失时的配对方差比较
Several tests for the equality of variances in the paired case with incomplete data on both responses are compared using Monte Carlo simulations. The main result is the recommendation to use a test due to Ekbohm (1981) for cases with moderate correlations. A new test proposed in this paper may be the best choice when the correlation is high.
双响应均有缺失时配对数据的方差比较
Several tests for the equality of variances in the paired case with incomplete data on both responses are compared using Monte Carlo simulations. The main result is the recommendation to use a test due to Ekbohm (1981) for cases with moderate correlations. A new test proposed in this paper may be the best choice when the correlation is high.
双方响应均有缺失时配对均值的比较
Five procedures for testing the equality of two correlated means with incomplete data on both responses are compared by using Monte Carlo studies; three procedures were suggested by Lin & Stivers (1974) and two are suggested in this paper. The results are that the two tests based on a modified maximum likelihood estimator are to be preferred, the one due to Lin & Stivers when the number of complete pairs is large and the one proposed in this paper otherwise, provided the…
一个响应存在缺失时的配对均值比较
Several procedures have been suggested for estimating the mean difference from correlated data with missing observations on one response. By Monte Carlo studies it is shown that a statistic due to Morrison is to be preferred, unless there isa large variance difference.
双响应均有缺失时配对均值的比较
Five procedures for testing the equality of two correlated means with incomplete data on both responses are compared by using Monte Carlo studies; three procedures were suggested by Lin & Stivers (1974) and two are suggested in this paper. The results are that the two tests based on a modified maximum likelihood estimator are to be preferred, the one due to Lin & Stivers when the number of complete pairs is large and the one proposed in this paper otherwise, provided the…
一个响应存在缺失时的配对均值比较
Several procedures have been suggested for estimating the mean difference from correlated data with missing observations on one response. By Monte Carlo studies it is shown that a statistic due to Morrison is to be preferred, unless there isa large variance difference.