Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome.
Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome.
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DOI：
10.1093/ije/dyu005
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发表时间：
2014-06
影响因子：
7.7
通讯作者：
Burgess S
中科院分区：
文献类型：
--
作者：
Burgess S
背景：样本量计算是流行病学研究规划的重要工具。在孟德尔随机化研究中经常需要大样本量。方法与结果：为研究者提供了资源，以进行样本量和功效计算，用于孟德尔随机化和二元结局。我们首先提供公式的连续结果的情况下，然后类似的二元结果的情况下的公式。该公式对单个工具变量有效，该工具变量可以是单个遗传变体或包含多个变体的等位基因得分。对于风险因素对结果的因果效应以及风险因素与工具变量之间的平方相关性的给定值，提供图表以给出80%把握度所需的样本量。R代码和在线计算器工具可用于计算给定这些参数的选定功效水平所需的样本量，以及给定选定样本量和这些参数的功效。结论：给定功效的孟德尔随机化研究所需的样本量在很大程度上取决于工具变量解释的风险因素的方差比例。将多个变异纳入等位基因评分以解释风险因子的更多变异将提高功效，但必须注意不要因纳入无效变异而引入偏倚。
Background: Sample size calculations are an important tool for planning epidemiological studies. Large sample sizes are often required in Mendelian randomization investigations. Methods and results: Resources are provided for investigators to perform sample size and power calculations for Mendelian randomization with a binary outcome. We initially provide formulae for the continuous outcome case, and then analogous formulae for the binary outcome case. The formulae are valid for a single instrumental variable, which may be a single genetic variant or an allele score comprising multiple variants. Graphs are provided to give the required sample size for 80% power for given values of the causal effect of the risk factor on the outcome and of the squared correlation between the risk factor and instrumental variable. R code and an online calculator tool are made available for calculating the sample size needed for a chosen power level given these parameters, as well as the power given the chosen sample size and these parameters. Conclusions: The sample size required for a given power of Mendelian randomization investigation depends greatly on the proportion of variance in the risk factor explained by the instrumental variable. The inclusion of multiple variants into an allele score to explain more of the variance in the risk factor will improve power, however care must be taken not to introduce bias by the inclusion of invalid variants.
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影响因子：
5
作者：
Palmer, Tom M.;Sterne, Jonathan A. C.;Didelez, Vanessa
通讯作者：
Didelez, Vanessa
影响因子：
7.7
作者：
Burgess, Stephen;Thompson, Simon G.
通讯作者：
Thompson, Simon G.
孟德尔随机分组：它如何 - 不能 - 螺旋 - 证实营养与癌症之间的因果关系。
DOI：
10.1158/1940-6207.capr-08-0070
发表时间：
2009-02
期刊：
Cancer prevention research (Philadelphia, Pa.)
影响因子：
--
作者：
Schatzkin A;Abnet CC;Cross AJ;Gunter M;Pfeiffer R;Gail M;Lim U;Davey-Smith G
通讯作者：
Davey-Smith G
影响因子：
7.7
作者：
Greenland, S
通讯作者：
Greenland, S
影响因子：
2
作者：
Harbord, Roger M.;Didelez, Vanessa;Sheehan, Nuala A.
通讯作者：
Sheehan, Nuala A.