Age–period–cohort (APC) models are widely used for studying time trends of disease incidence or mortality. Model identifiability has become less of a problem with Bayesian APC models. These models are usually based on random walk (RW1, RW2) smoothing priors. For long and complex time series...
2. Bayesian APC models Inthefollowingleti=i,...,I denotetheindexoftheagegroup, j =1,...,J theindexof the period and k =1,...,K the index of the birth cohort. The cohort index can explicitly be computedfromagegroupandperiod indexofanincidence, seealsoFigure1; ifageand period areon...
The Bayesian age-period-cohort models were used to projectrehabilitation needs.Results: The number of prevalent cases and years lived with disability (YLD) countsin need of musculoskeletal rehabilitation increased greatly in China from 1990 to2019. There will be 465.9 million Chinese people in need ...
This model has been shown to have better accuracy compared to other forecasting models in previous studies [10,11,12]. The BAPC model is based on the age-period-cohort [13] (APC) model, which assumes an association between the incidence or mortality rates and age structure and population ...
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 ...
基金 supported by grants from the Shandong Provincial Natural Science Foundation[ZR2020MH188,ZR2021MH051] Project of Science and Technology Development Plan of Traditional Chinese Medicine in Shandong Province[Grant/Award Number:2019-0424] 2021 Youth Innovation Talent Introduction and Education Program of...
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 ...
Whether you are working with customer data or tracking election polls, Pandas and StatsModels provide powerful tools for getting insights from survey data. In this tutorial, we’ll start with the basics and work up to age-period-cohort analysis and logistic regression. As examples, we’ll use ...
We performed an age-period-cohort analysis of annual trends of suicide rates by age group in Japan using a Bayesian cohort model. With the help of the Nakamura method, we have been able to break down the effects of age, time period, cohort, and the age-by-period interaction. The cohort...
Finally, trends in the years following 2019 were predicted by Bayesian age–period–cohort (BAPC) models. We showed that, globally, the number of prevalent cases was 3,881,624 [95% uncertainty interval (UI): 3,301,963 to 4,535,045] in 1990 and increased to 7,473,400 (95% UI: 6,...