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Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014
The Journal of the Royal Statistical Society, Series A (Statistics in Society) ( IF 2 ) Pub Date : 2021-03-23 , DOI: 10.1111/rssa.12685
Zoë Fannon 1 , Christiaan Monden 1 , Bent Nielsen 1
Affiliation  

We develop an age-period-cohort model for repeated cross-section data with individual covariates, which identifies the non-linear effects of age, period and cohort. This is done for both continuous and binary dependent variables. The age, period and cohort effects in the model are represented by a parametrization with freely varying parameters that separates the identified non-linear effects and the unidentifiable linear effects. We develop a test of the parametrization against a more general ‘time-saturated’ model. The method is applied to analyse the obesity epidemic in England using survey data. The main non-linear effects we find in English obesity data are age-related among women and cohort-related among men.

中文翻译:

建模非线性年龄-周期-队列效应和协变量,并应用于 2001-2014 年英国肥胖症

我们为具有个体协变量的重复横截面数据开发了一个年龄-时期-队列模型,该模型确定了年龄、时期和队列的非线性效应。这对连续和二元因变量都是如此。模型中的年龄、时期和队列效应由参数化表示,该参数化具有自由变化的参数,可将已识别的非线性效应和无法识别的线性效应分开。我们针对更一般的“时间饱和”模型开发了参数化测试。该方法用于使用调查数据分析英国的肥胖流行情况。我们在英国肥胖数据中发现的主要非线性效应在女性中与年龄相关,在男性中与队列相关。
更新日期:2021-03-23
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