论文信息 - A flexible Bayesian algorithm for sample size calculations in misclassified data

A flexible Bayesian algorithm for sample size calculations in misclassified data

The problem of obtaining a flexible and easy to implement algorithm in order to derive the optimal sample size when the data are subject to misclassification is critical to practitioners. The topic is addressed from the Bayesian point of view where a special structure of the a priori parameter information is investigated. The proposed methodology is applied in specific examples.

Hector E. Nistazakis | Athanassios Katsis

[1] D. Lindley. The choice of sample size , 1997 .

[2] Gunel Erdogan,et al. A bayesian analysis of the multinomial model for a dichotomous response with nonrespondents , 1984 .

[3] P Bélisle,et al. Bayesian and mixed Bayesian/likelihood criteria for sample size determination. , 1997, Statistics in medicine.

[4] V. M. Raats,et al. Double checking auditors: A Bayesian approach , 2003 .

[5] C. Adcock. Sample size determination : a review , 1997 .

[6] C. J. Adcock,et al. The choice of sample size. Commentaries. Author's reply , 1997 .

[7] L. Joseph,et al. Bayesian sample size determination for estimating binomial parameters from data subject to misclassification , 2000 .

[8] G. Somes,et al. Beyond Normality: The Predictive Value and Efficiency of Medical Diagnoses R. S. Galen and S. R. Gambino. New York, Wiley, 1975, 237 pp, $14.95 , 1976 .

[9] Alaattin Erkanli,et al. Optimal Bayesian two-phase designs , 1998 .

[10] Sheldon M. Ross. Bayesians Should Not Resample a Prior Sample to Learn about the Posterior , 1996 .

[11] Athanassios Katsis,et al. Sample size for testing homogeneity of two a priori dependent binomial populations using the Bayesian approach , 2004, Adv. Decis. Sci..

[12] Alan E. Gelfand,et al. Bayesian statistics without tears: A sampling-resampling perspective , 1992 .