References
- Anderson, T. W. (1957). Maximum likelihood estimates for a multivariate normal distribution when some observations are missing. Journal of the American Statistical Association, 52(278), 200–203.
- Bhargava, R. (1962). Multivariate tests of hypotheses with incomplete data. Technical report No. 3. Stanford, CA: Applied Mathematics and Statistics Laboratories, Stanford University.
- Chang, W.-Y., & Richards, D. St. P. (2009). Finite-sample inference with monotone incomplete multivariate normal data, I. Journal of Multivariate Analysis, 100(9), 1883–1899.
- Jinadasa, K. G., & Tracy, D. S. (1992). Maximum likelihood estimation for multivariate normal distribution with monotone sample. Communications in Statistics – Theory and Methods, 21(1), 41–50.
- Kanda, T., & Fujikoshi, Y. (1998). Some basic properties of the MLE’s for a multivariate normal distribution with monotone missing data. American Journal of Mathematical and Management Sciences, 18(1–2), 161–190.
- Krishnamoorthy, K., & Pannala, M. K. (1999). Confidence estimation of a normal mean vector with incomplete data. The Canadian Journal of Statistics, 27(2), 395–407.
- Rao, C. R. (1956). Analysis of dispersion with incomplete observations on one of the characters. Journal of the Royal Statistical Society: Series B, 18(2), 259–264.
- Seko, N. (2012). Tests for mean vectors with two-step monotone missing data for the k-sample problem. SUT Journal of Mathematics, 48(2), 213–229.
- Seko, N., Kawasaki, T., & Seo, T. (2011). Testing equality of two mean vectors with two-step monotone missing data. American Journal of Mathematical and Management Sciences, 31(1–2), 117–135.
- Seko, N., Yamazaki, A., & Seo, T. (2012). Tests for mean vector with two-step monotone missing data. SUT Journal of Mathematics, 48(1), 13–36.
- Seo, T., Mano, S., & Fujikoshi, Y. (1994). A generalized Tukey conjecture for multiple comparisons among mean vectors. Journal of the American Statistical Association, 89(426), 676–679.
- Seo, T., & Siotani, M. (1992). The multivariate Studentized range and its upper percentiles. Journal of the Japan Statistical Society, 22(2), 123–137.
- Yagi, A., & Seo, T. (2014). A test for mean vector and simultaneous confidence intervals with three-step monotone missing data. American Journal of Mathematical and Management Sciences, 33(3), 161–175.
- Yagi, A., & Seo, T. (2015a). Tests for mean vectors with two-step and three-step monotone samples. Josai Mathematical Monographs, 8, 49–71.
- Yagi, A., & Seo, T. (2015b). Tests for equality of mean vectors and simultaneous confidence intervals with two-step or three-step monotone missing data patterns. American Journal of Mathematical and Management Sciences, 34(3), 213–233.
- Yu, J., Krishnamoorthy, K., & Pannala, K. M. (2006). Two-sample inference for normal mean vectors based on monotone missing data. Journal of Multivariate Analysis, 97(10), 2162–2176.