Construction and application of joinpoint regression model for series cumulative data
10.3760/cma.j.issn.0253-9624.2019.10.024
- VernacularTitle: 序列累计和数据Joinpoint回归模型构建及应用研究
- Author:
Siqing ZENG
1
Author Information
1. Guangdong Provincial Institute of Public Health/Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
- Publication Type:Journal Article
- Keywords:
Models, statistical;
Regression analysis;
Series cumulative data
- From:
Chinese Journal of Preventive Medicine
2019;53(10):1075-1080
- CountryChina
- Language:Chinese
-
Abstract:
Based on the principle of Joinpoint regression (JPR) model and the additivity of Poisson distribution, this paper constructed a JPR model for series cumulative data. The notifiable incidence number of dengue fever cases per week and weekly cumulative data in Guangdong province from 2008 to 2017 were analyzed, using (mean squared errors) MSE and (mean absolute percentage error) MAPE to evaluate different models. Except for 2015, the MSE and MAPE produced from the logarithmic linear JPR model based on weekly cumulative incidence number were smaller than those based on the weekly data. The fitting accuracy of JPR model for series cumulative data for trend analysis had been improved significantly. This model could be applied to the analysis of the trend change and the prediction of staged cumulative incidence.
