Comparison of generalized estimating equations (GEE), mixed effects models (MEM) and repeated measures ANOVA in analysis of menorrhagia data

P. Naseri, H. Majd, N. Kariman, Atefeh Sourtiji
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引用次数: 20

Abstract

Menorrhagia is one of the most common gynecological problem and leading causes of poor quality of life and iron deficiency anemia in women of reproductive age. Research in gynecological field relies heavily on repeated measure designs. Repeated measure studies are helpful in understanding how factors of interest change over time. Our goal is to apply statistical methods which are appropriate for analyzing repeated measure data such as gynecological data. Three statistical methods were performed by data collection from 100 patients with menorrhagia. One-hundred patients were randomly assigned to two groups, i.e. intervention group (Urtica Dioica and mefenamic acid) and control group (placebo and mefenamic acid) with an equal size of 50. In this study, generalized estimating equations (GEE) and mixed effects models (MEM) were used for analyzing menorrhagia data to determine the effect of hydroalcoholic extract of Urtica Dioica on Menorrhagia. Finally, these methods are compared to the conventional repeated measures ANOVA (RM-ANOVA). Based on the results, the three methods are found to be similar in terms of statistical estimation, the amount of bleeding before and after treatment between and within groups was compared. Results showed the average amount of bleeding was reduced significantly (P˂0/001). The average menorrhagia score in the third month (second cycles after intervention) were 91.38(71.432) and 149.40(127.823) in Urtica Dioica and control groups, respectively. The difference between the two groups was statistically significant (p =0.036). Because their advantages, GEE and MEM should be strongly considered for the analysis of repeated measure data. In particular, GEE should be utilized to explore overall average effects. When in addition to overall average effects, subject-specific effects are of primary interest, MEM should be utilized. With respect to these methods, it seems the extract of Urtica Dioica can be effective in reducing the amount of menstrual bleeding in women of reproductive age with Menorrhagia.
广义估计方程(GEE)、混合效应模型(MEM)和重复测量方差分析在月经过多资料分析中的比较
月经过多是最常见的妇科问题之一,也是育龄妇女生活质量差和缺铁性贫血的主要原因。妇科研究在很大程度上依赖于重复测量设计。重复测量研究有助于理解感兴趣的因素如何随时间变化。我们的目标是应用适合于分析重复测量数据的统计方法,如妇科数据。对100例月经过多患者的资料进行了三种统计方法。100例患者随机分为干预组(荨麻加甲芬那酸)和对照组(安慰剂加甲芬那酸)两组,各50例。本研究采用广义估计方程(generalized estimation equation, GEE)和混合效应模型(mixed effects models, MEM)对月经数据进行分析,以确定苦楝水醇提取物对月经过多的影响。最后,将这些方法与传统的重复测量方差分析(RM-ANOVA)进行比较。根据结果,发现三种方法在统计估计上是相似的,比较组间和组内治疗前后出血量。结果显示,平均出血量明显减少(P小于0/001)。第3个月(干预后第2个周期)平均月经过多评分分别为91.38分(71.432分)和149.40分(127.823分)。两组间差异有统计学意义(p =0.036)。由于GEE和MEM的优点,在重复测量数据的分析中应大力考虑它们。特别是,应该利用GEE来探索总体平均效果。除了总体平均效应外,当主要关注特定主题效应时,应利用MEM。关于这些方法,似乎荨麻提取物可以有效地减少月经过多的育龄妇女的月经出血量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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