Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.
Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.
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DOI：
10.1186/1471-2288-14-49
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发表时间：
2014-04-09
影响因子：
4
通讯作者：
Sim J
中科院分区：
文献类型：
--
作者：
Egbewale BE;Lewis M;Sim J
方差分析（ANOVA）、变化评分分析（CSA）和协方差分析（ANCOVA）对随机对照试验中基线不平衡的反应不同。然而，没有实证研究似乎已经量化的差异偏倚和精度的估计来自这些分析方法，其相对的统计力量，在关键试验特征的水平组合。因此，本模拟研究使用模拟试验数据检查了这三种分析的相对偏倚、精密度和统计功效。评估了126个假设试验场景（126000个数据集），每个场景都使用以下水平的组合模拟连续数据：治疗效果;前后测相关性;基线失衡的方向和幅度。计算每种情况下每种分析方法的偏倚、精密度和把握度。与ANCOVA产生的无偏估计相比，ANOVA和CSA都受到偏差的影响，与前后测相关和基线不平衡的方向有关。此外，ANOVA和CSA的精确度低于ANCOVA，特别是当前后测相关≥ 0.3时。当组在基线时平衡时，ANCOVA至少与其他分析一样有效。显然，方差分析和CSA在某些不平衡方面实现了更大的功效。在治疗前和治疗后评分之间的一系列相关性以及基线不平衡的不同水平和方向上，ANCOVA仍然是分析RCT中连续结局的最佳统计方法，包括偏倚、精确度和统计功效。
Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.
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影响因子：
2.3
作者：
Ciolino, Jody D.;Martin, Renee H.;Palesch, Yuko Y.
通讯作者：
Palesch, Yuko Y.
影响因子：
105.7
作者：
Kahan, Brennan C.;Morris, Tim P.
通讯作者：
Morris, Tim P.
DOI：
10.1016/0197-2456(85)90093-5
发表时间：
1985-01-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
EGGER, MJ;COLEMAN, ML;WILLIAMS, HJ
通讯作者：
WILLIAMS, HJ
影响因子：
1.1
作者：
Overall, J E;Doyle, S R
通讯作者：
Doyle, S R
DOI：
10.1136/bmj.e7586
发表时间：
2013-01-08
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Chan AW;Tetzlaff JM;Gøtzsche PC;Altman DG;Mann H;Berlin JA;Dickersin K;Hróbjartsson A;Schulz KF;Parulekar WR;Krleza-Jeric K;Laupacis A;Moher D
通讯作者：
Moher D