Construction and application of joinpoint regression model for series cumulative data / 中华预防医学杂志
Chinese Journal of Preventive Medicine
; (12): 1075-1080, 2019.
Article
in Chinese
| WPRIM (Western Pacific)
| ID: wpr-797033
Responsible library:
WPRO
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.
Full text:
Available
Health context:
Neglected Diseases
Health problem:
Dengue
Database:
WPRIM (Western Pacific)
Type of study:
Prognostic study
Language:
Chinese
Journal:
Chinese Journal of Preventive Medicine
Year:
2019
Document type:
Article