TY - JOUR
T1 - The weighted general linear model for longitudinal medical cost data–an application in colorectal cancer
AU - Hwang, Y. T.
AU - Huang, C. H.
AU - Yeh, W. L.
AU - Shen, Y. D.
PY - 2017/1/25
Y1 - 2017/1/25
N2 - Identifying cost-effective decisions that can take into account of medical cost and health outcome is an important issue under very limited resources. Analyzing medical costs has been challenged owing to skewness of cost distributions, heterogeneity across samples and censoring. When censoring is due to administrative reasons, the total cost might be related to the survival time since longer survivals are likely to be censored and the corresponding total cost will be censored as well. This paper uses the general linear model for the longitudinal data to model the repeated medical cost data and the weighted estimating equation is used to find more accurate estimates for the parameter. Furthermore, the asymptotic properties for the proposed model are discussed. Simulations are used to evaluate the performance of estimators under various scenarios. Finally, the proposed model is implemented on the data extracted from National Health Insurance database for patients with the colorectal cancer.
AB - Identifying cost-effective decisions that can take into account of medical cost and health outcome is an important issue under very limited resources. Analyzing medical costs has been challenged owing to skewness of cost distributions, heterogeneity across samples and censoring. When censoring is due to administrative reasons, the total cost might be related to the survival time since longer survivals are likely to be censored and the corresponding total cost will be censored as well. This paper uses the general linear model for the longitudinal data to model the repeated medical cost data and the weighted estimating equation is used to find more accurate estimates for the parameter. Furthermore, the asymptotic properties for the proposed model are discussed. Simulations are used to evaluate the performance of estimators under various scenarios. Finally, the proposed model is implemented on the data extracted from National Health Insurance database for patients with the colorectal cancer.
KW - General linear model
KW - inverse probability weighted method
KW - longitudinaldata
KW - medical cost
KW - proportional hazards model
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U2 - 10.1080/02664763.2016.1169255
DO - 10.1080/02664763.2016.1169255
M3 - Article
AN - SCOPUS:84964026275
SN - 0266-4763
VL - 44
SP - 288
EP - 307
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
IS - 2
ER -