random forests model
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Author(s):  
Haewon BYEON

Background: We aimed to develop a model predicting the participation of the elderly in a cognitive health program using the random forest algorithm and presented baseline information for enhancing cognitive health. Methods: This study analyzed the raw data of Seoul Welfare Panel Study (SWPS) (20), which was surveyed by Seoul Welfare Foundation for the residents of Seoul from Jun 1st to Aug 31st, 2015. Subjects were 2,111 (879 men and 1232 women) persons aged 60 yr and older living in the community who were not diagnosed with dementia. The outcome variable was the intention to participate in a cognitive health promotion program. A prediction model was developed by the use of a Random forests and the results of the developed model were compared with those of a decision tree analysis based on classification and regression tree (CART). Results: The random forests model predicted education level, subjective health, subjective friendship, subjective family bond, mean monthly family income, age, smoking, living with a spouse or not, depression history, drinking, and regular exercise as the major variables. The analysis results of test data showed that the accuracy of the random forests was 72.3% and that of the CART model was 70.9%. Conclusion: It is necessary to develop a customized health promotion program considering the characteristics of subjects in order to implement a program effectively based on the developed model to predict participation in a cognitive health promotion program.


Econometrics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 49 ◽  
Author(s):  
Jau-er Chen ◽  
Chen-Wei Hsiang

We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also apply the proposed procedure to reinvestigate the distributional effect of 401(k) participation on net financial assets, and the quantile earnings effect of participating in a job training program.


2019 ◽  
Vol 658 ◽  
pp. 936-946 ◽  
Author(s):  
Tingting Ye ◽  
Naizhuo Zhao ◽  
Xuchao Yang ◽  
Zutao Ouyang ◽  
Xiaoping Liu ◽  
...  

2018 ◽  
Vol 28 (3) ◽  
pp. 757-775 ◽  
Author(s):  
Maher Ibrahim Sameen ◽  
Biswajeet Pradhan ◽  
Saro Lee

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