ANALYSIS OF COVARIANCE IN PARALLEL-GROUP CLINICAL-TRIALS WITH PRETREATMENT BASELINES
ANALYSIS OF COVARIANCE IN PARALLEL-GROUP CLINICAL-TRIALS WITH PRETREATMENT BASELINES
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DOI：
10.2307/2531543
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发表时间：
1987-12-01
期刊：
影响因子：
1.9
通讯作者：
CRAGER, MR
中科院分区：
文献类型：
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作者：
CRAGER, MR
协方差分析（ANCOVA）技术常用于临床试验分析，以试图解释治疗前基线值变化对同一变量治疗后测量结果的影响。结果变量的基线测量通常是随机变量，这违反了协变量值固定的ANCOVA假设。因此，对于本申请，治疗效应的常规ANCOVA假设检验可能无效，ANCOVA斜率参数估计值存在偏倚。然而，我们表明，如果治疗前-治疗后测量值具有二元正态分布，则（1）具有独立于协变量的残差的ANCOVA模型是治疗前和治疗后测量值之间关系的有效表达;（ii）通常的（固定协变量分析）斜率参数和治疗效应对比的ANCOVA估计值无偏倚;和（iii）通常的ANCOVA治疗效果对比t检验是治疗效果的有效显著性检验。此外，只要治疗效应的幅度不依赖于结局变量的“真实”治疗前值，真实斜率参数必须位于区间（0，1）内，ANCOVA模型具有明确的解释，即对应用于治疗后-治疗前差异的方差分析模型进行调整（基于受试者间和受试者内变异性）。
Analysis of covariance (ANCOVA) techniques are often employed in the analysis of clinical trials to try to account for the effects of varying pretreatment baseline values of an outcome variable on posttreatment measurements of the same variable. Baseline measurements of outcome variables are typically random variables, which violates the usual ANCOVA assumption that covariate values are fixed. Therefore, the usual ANCOVA hypothesis tests of treatment effects may be invalid, and the ANCOVA slope parameter estimator biased, for this application. We show, however, that if the pretreatment-posttreatment measurements have a bivariate normal distribution, then (1) the ANCOVA model with residual error independent of the covariate is a valid expression of the relationship between pretreatment and posttreatment measurements; (ii) the usual (fixed-covariate analysis) ANCOVA estimates of the slope parameter and treatment effect contrasts are unbiased; and (iii) the usual ANCOVA treatment effect contrast t-tests are valid significance tests for treatment effects. Moreover, as long as the magnitudes of the treatment effects do not depend on the "true" pretreatment value of the outcome variable, the true slope parameter must lie in the interval (0,1) and the ANCOVA model has a clear interpretation as an adjustment (based on between- and within-subject variability) to an analysis of variance model applied to the posttreatment-pretreatment differences.