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Details for article 2 of 10 found articles
| Title: |
A monte carlo investigation of a statistic for a bivariate missing data problem |
| Author: |
Woolson, R.F. Leeper, J.D. Cole, J.W.L. Clarke, W.R. |
| Appeared in: |
Communications in statistics |
| Paging: | Volume 5 (1976) nr. 7 pages 681-688 |
| Year: |
1976 |
| Contents: |
Testing the equal means hypothesis of a bivariate normal distribution with homoscedastic varlates when the data are incomplete is considered. If the correlational parameter, ρ, is known, the well-known theory of the general linear model is easily employed to construct the likelihood ratio test for the two sided alternative. A statistic, T, for the case of ρ unknown is proposed by direct analogy to the likelihood ratio statistic when ρ is known. The null and nonnull distribution of T is investigated by Monte Carlo techniques. It is concluded that T may be compared to the conventional t distribution for testing the null hypothesis and that this procedure results in a substantial increase in power-efficiency over the procedure based on the paired t test which ignores the incomplete data. A Monte Carlo comparison to two statistics proposed by Lin and Stivers (1974) suggests that the test based on T is more conservative than either of their statistics. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 2 of 10 found articles
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