Bayesian age-period-cohort modeling and prediction: BAMP. J Stat Software. 2007;21:1-15.Schmid Volker J., Knorr-Held Leonard. Bayesian age-period-cohort modeling and prediction – BAMP. Journal of Statistical Software . 2007; 21 (8) doi: 10.18637/jss.v021.i08. Available: http://www....
BayesianAge-Period-CohortModelingand Prediction–BAMP VolkerJ.Schmid ImperialCollegeLondon LeonhardHeld Universit¨atZ¨urich Abstract ThesoftwarepackageBAMPprovidesamethodofanalyzingincidenceormortality dataontheLexisdiagram,usingaBayesianversionofanage-period-cohortmodel.A ...
After accounting for period deviations, the risk of cancer incidence exhibited an exponential increase with age for both sexes. Based on the Bayesian age-period-cohort analysis, it is estimated that there will be around 210,701 new cancer cases in 2027. Moreover, the Age-Standardized Rate (...
Bayesian hierarchical age-period-cohort models withtime-structured effects: An application to religious votingin the US, 1972–2008qDaniel StegmuellerDepartment of Government, University of Essex, Colchester, CO4 3SQ United Kingdoma r t i c l e i n f oArticle history:Received 15 May 2013Acce...
The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. A hierarchical model is assumed with a binomial model in the first-stage. As smoothing priors for the age, period and cohort param...
(p,0.001) during the30 year period. There were two second order and thus identifiable changes: (1) around the mid-1920scohort curve representing an age-period interaction masquerading as a cohort change that denotes thefirst availability of Pap testing during the 1960s concentrated among women ...
We used a well-established hierarchical Bayesian Age Period Cohort (APC) model, which works under the assumption that variability in incidence data can be explained by age, period and cohort effects. We fitted this model to observed CHD mortality rate trends from 1982 to 2006. We then used ...
Age cohort analysis is commonly used to estimate population parameters of animals that are harvested. The method is based on known age at death that can be used for Bayesian hierarchical growth models. It is interesting to see if similar methods, hitherto conducted on long‐living species, can ...
was also not considered in the model due to its high correlations with the percent of age groups 45–64, and 65 years and over, with the correlation coefficients of − 0.6 and − 0.8, respectively. Simultaneously, the variance inflation factor (VIF) was used to verify multicollinearity. ...
Participants completed one session of the Museum Averaging Task at a computer just as the other cohort had completed the prescan session of the Museum Inference Task; there was no scan session. Three participants’ data were excluded from the analysis because their responses reflected disengagement ...