id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-265138-i5m3ax7g	Wang, Xi-Ling	Model Selection in Time Series Studies of Influenza-Associated Mortality	2012-06-20		.txt	text/plain	4196	240	45	METHODS: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. CONCLUSIONS: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. Four model selection criteria were considered in this study: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV). Two recent studies in Canada and Hong Kong have demonstrated the estimates of influenza-associated hospitalization derived from Poisson regression models reasonably matched the numbers of patients with laboratory confirmed influenza infections [17, 29] .	./cache/cord-265138-i5m3ax7g.txt	./txt/cord-265138-i5m3ax7g.txt