Using weighted regression model for estimating cohort effect in age-period contingency table data

Abstract

Go to:\nBackground\nRecently, the multiphase method was proposed to estimate cohort effects after removing the effects of age and period in age-period contingency table data. Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and is strongly associated with cirrhosis, due to both alcohol and viral etiologies. In epidemiology, age-period-cohort (APC) model can be used to describe (or predict) the secular trend in HCC mortality.\n\nGo to:\nResults\nThe confidence interval (CI) of the weighted estimates was found to be relatively narrow (compared to unweighted estimates). Moreover, for males, the mortality trend reverses itself during 2006–2010 was found from an increasing trend into a slightly deceasing trend. For females, the increasing trend reverses (earlier than males) itself during 2001–2005.\n\nGo to:\nConclusions\nThe weighted estimation of the regression model is recommended for the multiphase method in estimating the cohort effects in age-period contingency table data.\n\nGo to:\nImpact\nThe regression model can be modified through the weighted average estimate of the effects with narrower CI of each cohort.\n\nGo to:\nMethods\nAfter isolating the residuals during the median polish phase, the final phase is to estimate the magnitude of the cohort effects using the regression model of these residuals on the cohort category with the weight equal to the occupied proportion according to the number of death of HCC in each cohort.