Blick and Hagen: Use of agreement measLires and latent class models to assess the reliability of classifying tfiermally marked otolitfis 9 



Richards, L. J., J, T. Schnute, A. R. Ki-onlund. and K. J. Beamish. 



1992. Statistical models for the analysis of ageing error. 

 Can. J. Fish. Aquat. Sci. 49:1801-1815. 



Regan, W. J., and B. Gladen. 



1978. Estimating prevalence from the results of a screening 

 test. Am. J. EpidemiologN' 107:71-76. 

 SAS Institute. 



1989. SAS/STAT user's guide, version 6, 4"' ed. SAS Insti- 

 tute, Gary, NC. 

 Statistical Sciences. 



1995. S-PLUS guide to statistical and mathematical analy- 

 sis, version 3.3. StatSci. Seattle, WA. 

 Vacek, P. M. 



1985. The effect of conditional dependence on the evalua- 

 tion of diagnostic tests. Biometrics 41:959-968. 

 Viana, M. A. G., V. Ramakrishnan, and P. S. Levy. 



1993. Bayesian analysis of prevalence from the results of 



small screening samples. Commun. Statist. Theory Melh. 

 22:57,5-.585. 

 Volk, E. C., S. L. Schroder, and K. L. PVesh. 



1990. Inducement of unique otolith banding patterns as a 

 practical means to mass-markjuvenile Pacific salmon. Am. 

 Fish. Soc. Symp. 7:203-215. 

 Walter, S. D. 



1984. Measuring the reliability of clinical data: the case 

 for using three observers. Rev. Epidem. et Sante Publ. 

 32:206-211. 

 Walter, S. D., and L. M. Ii-wig. 



1988. Estimation of test error rates, disease prevalence and 

 relative risk from misclassified data: a review. J. Clin. 

 Epidemiol. 41:923-937. 

 Yang, I., and M. P. Becker 



1997. Latent variable modeling of diagnostic accuracy. Bio- 

 metrics 53:948-958. 



