Public concern about, and desire for research into, the human health effects of marine plastic pollution: R script

Four R scripts, used for creating:
1) Sample wide weighted means of public concern for the human health impacts of 16 marine threats including marine plastic pollution and country level breakdowns of these means (Figures 1 & 3). A repeated measures ANOVA via a mixed linear effect model is also scripted which tests the effect of marine threat on concern level, as well as post hoc analysis testing the differences between marine threats.
2) Sample wide weighted means of public support for research into the human health implications of 15 marine research areas, including marine plastic pollution and country level breakdowns of these means (Figures 2 & 4). A repeated measures ANOVA via a mixed linear effect model is also scripted which tests the effect of marine research area on support level, as well as post hoc analysis testing the differences between marine research areas.
3) A data frame for multi-level regression analysis.
4) Multi-level modelling predicting public concern for and desire for research into marine plastic pollution, as well as mediation analysis formally testing the mediating effect of concern.

本数据集包含4个R脚本，可实现以下四类任务：
1) 计算16种海洋威胁（包括海洋塑料污染）对人类健康影响的公众关注度全样本加权均值，并给出该均值的国家层面细分结果（对应图1与图3）；脚本同时实现基于混合线性效应模型的重复测量方差分析，用于检验海洋威胁类型对公众关注度的影响，还包含事后检验分析以比较不同海洋威胁间的关注度差异。
2) 计算15个海洋研究领域（含海洋塑料污染相关研究）中，公众对该领域研究支持度的全样本加权均值，并给出该均值的国家层面细分结果（对应图2与图4）；脚本同时实现基于混合线性效应模型的重复测量方差分析，用于检验海洋研究领域对公众支持度的影响，还包含事后检验分析以比较不同海洋研究领域间的支持度差异。
3) 生成用于多级回归分析的数据框（data frame）。
4) 构建多级模型以预测公众对海洋塑料污染的关注度及开展相关研究的意愿，同时实现正式的中介效应分析，以检验关注度的中介作用。