The F-statistic tests whether a model (e.g., a linear or logistic regression model) with independent variables explains variation in the dependent variable, compared to a model with no independent variables.
F统计量用于检验包含自变量的模型（例如线性回归模型或逻辑回归模型）是否比不包含自变量的模型更能解释因变量的变异。
In MR analyses, the first-stage F-statistic (or just "F-statistic") can be used to test the strength of the association between the genetic instrumental variable (IV) and exposure of interest and the extent of the relative bias that is likely to occur in estimating the causal effect of the exposure on the outcome using the genetic IV. As a general rule, an F-statistic >10 indicates that the level of weak instrument bias is likely to be small. F-statistics should not be used to select IVs to avoid overfitting the estimation model. For example, an F-statistic of <10 does not indicate that an IV should not be used but, instead, it should be noted in the analysis that weak instrument bias should be a considered limitation. See Conditional F-statistic.
在孟德尔随机化（MR）分析中，第一阶段F统计量（或简称“F统计量”）可用于检验遗传工具变量（IV）与目标暴露之间的关联强度，以及使用遗传工具变量（IV）估计暴露对结局的因果效应时可能出现的相对偏倚程度。一般而言，F统计量＞10表明弱工具变量偏倚的程度可能较小。不应使用F统计量来选择工具变量（IVs），以避免过度拟合估计模型。例如，F统计量＜10并不意味着不应使用该工具变量（IV），而应在分析中注明，弱工具变量偏倚应被视为一个局限性。参见条件F统计量。
https://mr-dictionary.mrcieu.ac.uk/term/f-statistic/
