Correlating two continuous variables subject to detection limits in the context of mixture distributions

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 54, Issue 5, 2005, Pages 831-845

  Chu, Haitao ^a   Moulton, Lawrence H ^a   Mack, Wendy J ^b   Passaro, Douglas J ^c   Barroso, Paulo F ^d   Muñoz, Alvaro ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^c UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^d FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Bootstrap based information criterion; Correlation coefficient; Cross validation based information criterion; Human immunodeficiency virus; Left censoring; Likelihood ratio test; Mixture model; Model selection

Indexed keywords

EID: 27344451118     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2005.00512.x     Document Type: Article

References (22)

1. Barkan, S. E., Melnick, S. L., Preston-Martin, S., Weber, K., Kalish, L. A., Miotti, P., Young, M., Greenblatt, R., Sacks, H. and Feldman, J. (1998) The Woman's Interagency HIV Study. Epidemiology, 9, 117-125.
2. Barroso, P. F., Schechter, M., Gupta, P., Melo, M. F., Vieira, M., Murta, F. C., Souza, Y. and Harrison, L. H. (2000) Effect of antiretroviral therapy on HIV shedding in semen. Ann. Intern. Med, 133, 280-284.
3. Berk, K. N. and Lachenbruch, P A. (2002) Repeated measures with zeros. Statist. Meth. Med Res., 11, 303-316.
4. Celeux, G. and Soromenho, G. (1996) An entropy criterion for assessing the number of clusters in a mixture model. Classificn J., 13, 195-212.
5. Charnigo, R. and Sun, J. (2004) Testing homogeneity in a mixture distribution via the L2 distance between competing models. J. Am. Statist. Ass., 99, 488-498.
6. Chen, H., Chen, J. and Kalbfleisch, J. D. (2001) A modified likelihood ratio test for homogeneity in finite mixture models. J. R. Statist. Soc. B, 63, 19-29.
7. Efron, B. and Tibshirani, R. J. (1993) An Introduction to the Bootstrap. New York: CRC.
8. Ishiguro, M., Sakamoto, Y. and Kitagawa, G. (1997) Bootstrapping log-likelihood and EIC, an extension of AIC. Ann. Inst. Statist. Math., 49, 411-434.
9. Kullback, S. and Leibler, R. A. (1951) On information and sufficiency. Ann. Math. Statist., 22, 79-86.
10. Lyles, R. H., Williams, J. K. and Chuachoowong, R. (2001) Correlating two viral load assays with known detection limits. Biometrics, 57, 1238-1244.
11. McLachlan, G. J. (1987) On bootstrapping the likelihood ratio test statistic for the number of components in a normal mixture. Appl. Statist., 36, 318-324.
12. McLachlan, G. J. and Peel, D. (2001) Finite Mixture Models. New York: Wiley.
13. Moulton, L. H., Curriero, F. C. and Barroso, P. F. (2002) Mixture models for quantitative HIV RNA data. Statist. Meth. Med Res., 11, 317-325.
14. Moulton, L. H. and Halsey, N. A. (1995) A mixture model with detection limits for regression analyses of antibody response to vaccine. Biometrics, 51, 1570-1578.
15. Mulligan, R., Phelan, J. A., Brunelle, J., Redford, M., Pogoda, J. M., Nelson, E., Seirawan, H., Greenspan, J. S., Navazesh, M., Greenspan, D. and Alves, M. E. (2004) Baseline characteristics of participants in the oral health component of the Women's Interagency HIV Study. Commty Dent. Oral Epidem., 32, 86-98.
16. Richardson, S. and Green, P. J. (1997) On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. R. Statist. Soc. B, 59, 731-792; correction, 60 (1998), 661.
17. Self, S. G. and Liang, K. Y. (1987) Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard condition. J. Am. Statist. Ass., 82, 605-610.
18. Smyth, P. (2000) Model selection for probabilistic clustering using cross-validated likelihood. Statist. Comput., 10, 63-72.
19. Soromenho, G. (1993) Comparing approaches for testing the number of components in a finite mixture model. Computnl Statist., 9, 65-78.
20. Taylor, D. J., Kupper, L. L., Rappaport, S. M. and Lyles, R. H. (2001) A mixture for occupational exposure mean testing with a limit of detection. Biometrics, 57, 681-688.
21. Titterington, D. M., Smith, A. F. M. and Makov, U. E. (1985) Statistical Analysis of Finite Mixture Distributions. New York: Wiley.
22. Venables, W N. and Ripley, B. D. (2002) Modern Applied Statistics with S, 4th edn. New York: Springer.