A graphical approach to the interpretation of age-period-cohort data.
Two major obstacles to the routine application of age-period-cohort models are (1) the identification problem, and (2) the fact that separate interpretation of the coefficients of the model is seldom possible. We offer a practical solution to these obstacles that involves plotting the relation between the variable of interest and the age, period, and cohort variables in such a manner that nontrivial age, period, or cohort effects are readily recognized as particular types of features in the graph. These features remain recognizable in the presence of normal sampling variability. Examples are given for applying the technique to previously published mortality data.
School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, Burnaby, British Columbia.
J J
JJ
Weinkam
T D
TD
Sterling
D000367:Age Factors; D002170:Canada / Q000453:epidemiology; D015331:Cohort Studies; D006801:Humans; D008175:Lung Neoplasms / Q000401:mortality; D008433:Mathematics; D008545:Melanoma / Q000401:mortality; D015233:Models, Statistical; D012878:Skin Neoplasms / Q000401:mortality; D006113:United Kingdom / Q000453:epidemiology