Abstract
This is a survey of recent methods for the analysis of seasonal variation in medical research. These methods are effective even when the data show small amplitude and the sample size is small, two characteristics that are often present when one analyzes medical data for seasonal variation. The methods deal with both cases: one group and multiple groups. Also, these methods can be used to analyze different types of seasonal variation. Real-data examples are used to illustrate the application of these techniques.
References
Jones, R. H.; Ford, P. M.; Hamman, R. F. (1988) “Seasonality comparisons among groups using incidence data”, Biometrics 44: 1131–1144.
Marrero, O. (1979) Statistical Tests for Seasonality in Epidemiological Data. M.P.H. essay, Department of Epidemiology and Public Health, Yale University, New Haven, Connecticut.
Marrero, O. (1983) “The performance of several statistical tests for seasonality in monthly data”, Journal of Statistical Computation and Simulation 17: 275–296.
Marrero, O. (1984) “Statistical testing for seasonality in data with multiple peaks and troughs”, Biometrical Journal 26: 591–608.
Marrero, O. (1988) “The power of a nonparametric test for seasonality”, Biometrical Journal 30: 495–502.
Marrero, O. (1992) “A maximum rank-sum test for one-pulse variation in monthly data”, Biometrical Journal 34: 485–500.
Marrero, O. (1998) “Multigroup analysis of seasonal variation: assessing the homogeneity of multiple cyclically ordered multinomial distributions”, Environmetrics 9: 151–163.
Marrero, O. (1999) “L’analyse de la variation saisonnière quand l’amplitude et la taille sont faibles”, Revue Canadienne de Statistique (Canadian Journal of Statistics) 27: 875–882.
Strickland, A. D.; Shannon, K. (1982) “Studies in the etiology of extrahepatic biliary atresia: time-space clustering”, Journal of Pediatrics 100: 749–753.