This paper deals with the problem of linear regression for medical cost data when some study subjects are not followed for the full duration of interest so that their total costs are unknown. Standard survival analysis techniques are ill-suited to this type of censoring. The familiar normal equations for the least-squares estimation are modified in several ways to properly account for the incompleteness of the data. The resulting estimators are shown to be consistent and asymptotically normal with easily estimated variance–covariance matrices. The proposed methodology can be used when the cost database contains only the total costs for those with complete follow-up. More efficient estimators are available when the cost data are recorded in ...
When cost data are collected in a clinical study, interest centers on the between-treatment differen...
This paper suggests an approach to deal with an estimation problem which is often encountered in ana...
A system of seemingly unrelated regression equations is proposed for prognostic factor adjustment an...
Abstract: Economic evaluation of medical interventions has be-come an accepted, and often required, ...
This paper applies the inverse probability weighted least-squares method to predict total medical co...
Cost effectiveness methods have been applied to evaluate and compare different therapies for disease...
This paper applies the inverse probability weighted (IPW) least-squares method to estimate the effec...
A number of non-parametric estimators have been proposed to calculate average medical care costs in ...
This article investigates the way in which the presence of censored cost data in clinical trials sho...
Recent studies show that appropriate statistical analysis of cost data may lead to more cost-effecti...
Many analyses of healthcare costs involve use of data with varying periods of observation and right ...
Medical cost analysis is an important part of treatment evaluation. Since resources are limited in s...
In the statistical literature, life expectancy is usually characterised by the mean residual life fu...
Cost-effectiveness analysis is an essential part of the evaluation of new medical interventions. Whi...
OBJECTIVES: To assess the accuracy and precision of inverse probability weighted (IPW) least squares...
When cost data are collected in a clinical study, interest centers on the between-treatment differen...
This paper suggests an approach to deal with an estimation problem which is often encountered in ana...
A system of seemingly unrelated regression equations is proposed for prognostic factor adjustment an...
Abstract: Economic evaluation of medical interventions has be-come an accepted, and often required, ...
This paper applies the inverse probability weighted least-squares method to predict total medical co...
Cost effectiveness methods have been applied to evaluate and compare different therapies for disease...
This paper applies the inverse probability weighted (IPW) least-squares method to estimate the effec...
A number of non-parametric estimators have been proposed to calculate average medical care costs in ...
This article investigates the way in which the presence of censored cost data in clinical trials sho...
Recent studies show that appropriate statistical analysis of cost data may lead to more cost-effecti...
Many analyses of healthcare costs involve use of data with varying periods of observation and right ...
Medical cost analysis is an important part of treatment evaluation. Since resources are limited in s...
In the statistical literature, life expectancy is usually characterised by the mean residual life fu...
Cost-effectiveness analysis is an essential part of the evaluation of new medical interventions. Whi...
OBJECTIVES: To assess the accuracy and precision of inverse probability weighted (IPW) least squares...
When cost data are collected in a clinical study, interest centers on the between-treatment differen...
This paper suggests an approach to deal with an estimation problem which is often encountered in ana...
A system of seemingly unrelated regression equations is proposed for prognostic factor adjustment an...