Small-sample estimation of negative binomial dispersion, with applications to SAGE data

Biostatistics

Volumn 9, Issue 2, 2008, Pages 321-332

  Robinson, Mark D ^a,b   Smyth, Gordon K ^a  

^a WALTER AND ELIZA HALL INSTITUTE OF MEDICAL RESEARCH   (Australia)

^b UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Conditional likelihood; Dispersion; Negative binomial; Quantile adjustment; Serial analysis of gene expression

Indexed keywords

MESSENGER RNA;

ARTICLE; BINOMIAL DISTRIBUTION; BIOMETRY; EPIDEMIOLOGY; EXPRESSED SEQUENCE TAG; GENE EXPRESSION PROFILING; GENE LIBRARY; HUMAN; INFORMATION RETRIEVAL; METHODOLOGY; REGRESSION ANALYSIS; SAMPLE SIZE; STANDARD; STATISTICAL MODEL; STATISTICS;

BIAS (EPIDEMIOLOGY); BINOMIAL DISTRIBUTION; BIOMETRY; EXPRESSED SEQUENCE TAGS; GENE EXPRESSION PROFILING; GENE LIBRARY; HUMANS; INFORMATION STORAGE AND RETRIEVAL; LIKELIHOOD FUNCTIONS; REGRESSION ANALYSIS; RESEARCH DESIGN; RNA, MESSENGER; SAMPLE SIZE; STOCHASTIC PROCESSES; WEIGHTS AND MEASURES;

EID: 41149085992     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxm030     Document Type: Article

References (12)

1. BAGGERLEY, K. A., DENG, L., MORRIS, J. S. AND ALDAZ, C. M. (2004). Overdispersed logistic regression for sage: modelling multiple groups and covariates. BMC Bioinformatics 5, 144.
2. COX, D. R. AND REID, N. (1987). Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society, Series B 49, 1-39.
3. KAL, A. J., VAN ZONNEVELD, A. J., BENES, V., VAN DEN BERG, M., KOERKAMP, M. G., ALBERMANN, K., STRACK, N., RUIJTTER, J. M., RICHTER, A., DUJON, B. and others (1999). Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources. Molecular Biology of the Cell 10, 1859-1872.
4. LORD, D. (2006). Modeling motor vehicle crashes using poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter. Accident Analysis and Prevention 38, 751-766.
5. LU, J., TOMFOHR, J. K. AND KEPLER, T. B. (2005). Identifying differential expression in multiple sage libraries: an overdispersed log-linear model approach. BMC Bioinformatics 6, 165.
6. NELDER, J. A. (2000). Quasi-likelihood and pseudo-likelihood are not the same thing. Journal of Applied Statistics 27, 1007-1011.
7. NELDER, J. A. AND LEE, Y (1992). Likelihood, quasi-likelihood and pseudolikelihood: some comparisons. Journal of the Royal Statistical Society, Series B 54, 273-284.
8. SAHA, K. AND PAUL, S. (2005). Bias-corrected maximum likelihood estimator of the negative binomial dispersion parameter. Biometrics 61, 179-185.
9. SMYTH, G. K. (2003). Pearson's goodness of fit statistic as a score test statistic. In: Goldstein, D. R. (editor), Science and Statistics: A Festschrift for Terry Speed, IMS Lecture Notes - Monograph Series, Volume 40. Beachwood, OH: Institute of Mathematical Statistics, pp. 115-126.
10. SMYTH, G. K. AND VERBYLA, A. P. (1996). A conditional likelihood approach to residual maximum likelihood in generalized linear models. Journal of the Royal Statistical Society, Series B 58, 565-572.
11. VELCULESCU, V. E., ZHANG, L., VOGELSTEIN, B. AND KINZLER, K. W. (1995). Serial analysis of gene expression. Science 270, 484-487.
12. ZHANG, L., ZHOU, W., VELCULESCU, V. E., KERN, S. E., HRUBAN, R. H., STANLEY, S. R., HAMILTON, R., VOGELSTEIN, B. AND KINZLER, K. W. (1997). Gene expression profiles in normal and cancer cells. Science 276, 1268-1272.