On the one-sample location hypothesis for mixed bivariate data

Communications in Statistics - Theory and Methods

Volumn 29, Issue 11, 2000, Pages 2573-2581

  De Leon, A R ^a   Carriere K C ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Consistency; Likelihood ratio test; Location model; Power function

Indexed keywords

EID: 26844568919     PISSN: 03610926     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. Afifi, A. A., and Elashoff, R. M. (1969). Multivariate two sample tests with dichotomous and continuous variables. I. The location model. Ann. Math. Statist. 40, 290-298.
2. Bickel, P. J., and Doksum, K. A. (1977). Mathematical Statistics: Basic Ideas and Selected Topics. San Francisco: Holden Day.
3. Casella, G., and Berger, R. (1990). Statistical Inference. Belmont: Duxbury.
4. Catalano, P. J., and Ryan, L. M. (1992). Bivariate latent variable models for clustered discrete and continuous outcomes. J. Am. Statist. Assoc. 87, 651-658.
5. Fitzmaurice, G. M. and Laird, N. M. (1995). Regression models for a bivariate discrete and continuous outcome with clustering. J. Am. Statist. Assoc. 90, 845-852.
6. Johnson, N. L., and Kotz, S. (1970). Continuous Univariate Distributions-2. Boston: Houghton Mifflin.
7. Krzanowski, W. J. (1993). The location model for mixtures of categorical and continuous variables. J. Classification 10, 25-49.
8. Little, R. J., and Rubin, D. B. (1987). Statistical Analysis with Missing Data. New York: John Wiley.
9. Little, R. J., and Schluchter, M. D. (1985). Maximum likelihood estimation for mixed continuous and categorical data with missing values. Biometrika 72, 497-512.
10. Liu, C., and Rubin, D. B. (1998). Ellipsoidally symmetric extensions of the general location model for mixed categorical and continuous data. Biometrika 85, 673-688.
11. O'Brien, P. C. (1984). Procedures for comparing samples with multiple endpoints. Biometric 40, 1079-1087.
12. Olkin, I., and Tate, R. F. (1961). Multivariate correlation models with mixed discrete and continuous variables. Ann. Math. Statist. 32, 448-465 (correction in 36, 343-344).
13. Pocock, S. J., Geller, N. L., and Tsiatis, A. A. (1987). The analysis of multiple endpoints in clinical trials. Biometrics 43, 487-498.
14. Tate, R. F. (1955), Applications of correlation models for biserial data. J. Am. Statist. Assoc. 50, 1078-1095.
15. Tate, R. F. (1954). Correlation between a discrete and a continuous variable. Ann. Math. Statist. 25, 603-607.