Abstract
Because of the skewness of the distribution of medical costs, we consider modeling the median as well as other quantiles when establishing regression relationships to covariates. In many applications, the medical cost data are also right censored. In this article, we propose semiparametric procedures for estimating the parameters in median regression models based on weighted estimating equations when censoring is present. Numerical studies are conducted to show that our estimators perform well with small samples and the resulting inference is reliable in circumstances of practical importance. The methods are applied to a dataset for medical costs of patients with colorectal cancer.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 643-649 |
| Number of pages | 7 |
| Journal | Biometrics |
| Volume | 58 |
| Issue number | 3 |
| State | Published - Sep 2002 |
| Externally published | Yes |
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Keywords
- Cost analysis
- Estimating equation
- Median regression
- Simulated annealing
- Survival analysis
ASJC Scopus subject areas
- Agricultural and Biological Sciences(all)
- Public Health, Environmental and Occupational Health
- Agricultural and Biological Sciences (miscellaneous)
- Applied Mathematics
- Statistics and Probability
Cite this
Median regression with censored cost data. / Bang, Heejung; Tsiatis, Anastasios A.
In: Biometrics, Vol. 58, No. 3, 09.2002, p. 643-649.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Median regression with censored cost data
AU - Bang, Heejung
AU - Tsiatis, Anastasios A.
PY - 2002/9
Y1 - 2002/9
N2 - Because of the skewness of the distribution of medical costs, we consider modeling the median as well as other quantiles when establishing regression relationships to covariates. In many applications, the medical cost data are also right censored. In this article, we propose semiparametric procedures for estimating the parameters in median regression models based on weighted estimating equations when censoring is present. Numerical studies are conducted to show that our estimators perform well with small samples and the resulting inference is reliable in circumstances of practical importance. The methods are applied to a dataset for medical costs of patients with colorectal cancer.
AB - Because of the skewness of the distribution of medical costs, we consider modeling the median as well as other quantiles when establishing regression relationships to covariates. In many applications, the medical cost data are also right censored. In this article, we propose semiparametric procedures for estimating the parameters in median regression models based on weighted estimating equations when censoring is present. Numerical studies are conducted to show that our estimators perform well with small samples and the resulting inference is reliable in circumstances of practical importance. The methods are applied to a dataset for medical costs of patients with colorectal cancer.
KW - Cost analysis
KW - Estimating equation
KW - Median regression
KW - Simulated annealing
KW - Survival analysis
UR - http://www.scopus.com/inward/record.url?scp=0036712329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0036712329&partnerID=8YFLogxK
M3 - Article
C2 - 12229999
AN - SCOPUS:0036712329
VL - 58
SP - 643
EP - 649
JO - Biometrics
JF - Biometrics
SN - 0006-341X
IS - 3
ER -