Cost prediction models for the comparison of two groups
针对临床试验中缺乏患者成本数据的情况，提出一种成本预测模型，并给出估计组间平均成本方差的方法，附有应用实例。
For trial-based economic evaluation where patient-specific cost data are not routinely available, cost prediction models are commonly used to estimate total cost for each patient. Typically, multiple regression techniques are used on data from diagnosis-matched, non-trial patients (where patient-level cost data are available) to model cost as a function of covariates that are observed on the trial subjects (e.g. length of hospital stay, procedures, etc.). The estimated beta coefficients provide a means of estimating the total cost for each patient in the trial. However, the variability of the beta coefficients due the measurement and sampling error is seldom included in the overall variance expression for mean costs by treatment group. In this paper we provide a method for estimating this variance and provide an example application