乳腺癌Oncotype DX检测种族差异趋势分析数据集
用于调节效应分析的数据集，探索乳腺癌患者中Oncotype DX测试使用的种族差异趋势。
基本信息
资源简介
乳腺癌Oncotype DX检测种族差异趋势分析数据集
【一句话概览】
本文扩展R包“mma”用于调节分析，使第三变量效应可在调节变量不同水平上报告。方法采用树结构模型自动检测调节效应，支持分类与数值调节变量，并提出推断调节效应的算法与图形方法。最后应用于探索乳腺癌患者Oncotype DX复发检测使用中的种族差异趋势，发现2010至2015年该检测使用中无法解释的种族差异有所下降（来源 figshare，CC BY 4.0 许可）。
【数据集背景】
本数据集源站标题为《Inference on moderation effect with third-variable effect analysis – application to explore the trend of racial disparity in oncotype dx test for breast cancer treatment》。配套论文《Inference on moderation effect with third-variable effect analysis – application to explore the trend of racial disparity in oncotype dx test for breast cancer treatment》发表于 Journal of Applied Statistics（2021），DOI：10.1080/02664763.2021.1968358。项目资助方：This work was supported by National Institute on Minority Health and Health Disparities [R15MD012387].。源站首次发布：2021-08-28。
【数据内容】
源站原始描述：Third variable effect refers to the effect from a third variable that explains an observed relationship between an exposure and an outcome. Depending on whether there is causal relationship, typically, a third variable takes the format of a mediator or a confounder. A moderation effect is a special case of the third-variable effect, where the moderator and other variables have an interactive effect on the outcome. In this paper, we extend the R package ‘mma’ for moderation analysis so that third…
文件 cjas_a_1968358_sm8685.r 为文本内容，开头为：#Supplementary 1: codes for simulation studies library(mma) a0=0 a1=1 b0=0 b1=1 b2=1 b3=1 b4=1 b5=1 rho=0 mean1=c(0,0) n=200 #direct moderation:…
【数据结构与技术规格】
文件数 1 个，合计 9.70 KB。cjas_a_1968358_sm8685.r：text/plain，9.70 KB。数据集 DOI：10.6084/m9.figshare.16528947.v1。
【主题与分类】
源站学科分类：Biotechnology、Sociology、Biological Sciences not elsewhere classified、Mathematical Sciences not elsewhere classified、Science Policy、Plant Biology。主题标签：Confounding/mediation effect、health inequality、moderation/interactive effect、racial disparity、third-variable analysis。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://tandf.figshare.com/articles/dataset/Inference_on_moderation_effect_with_third-variable_effect_analysis_application_to_explore_the_trend_of_racial_disparity_in_oncotype_dx_test_for_breast_cancer_treatment/16528947
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Inference on moderation effect with third-variable effect analysis – application to explore the trend of racial disparity in oncotype dx test for breast cancer treatment. Taylor & Francis. Yu, Qingzhao; Zhang, Lu; Wu, Xiaocheng; Li, Bin
【使用注意】
· 源站最后修改于 2024-02-15，引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取（Figshare）
- 源站标题：Inference on moderation effect with third-variable effect analysis – application to explore the trend of racial disparity in oncotype dx test for breast cancer treatment
- DOI：10.6084/m9.figshare.16528947.v1
- 发布日期：2021-08-28
- 文件数：1 个
- 文件总体积：9.70 KB
- 源站页面：https://tandf.figshare.com/articles/dataset/Inference_on_moderation_effect_with_third-variable_effect_analysis_application_to_explore_the_trend_of_racial_disparity_in_oncotype_dx_test_for_breast_cancer_treatment/16528947
命令行下载
curl -L -o "cjas_a_1968358_sm8685.r" "https://ndownloader.figshare.com/files/30562290"
文件清单
cjas_a_1968358_sm8685.r（9.70 KB）
文件总体积 9.70 KB（源站 API 实测）。
数据加载示例（图像类）
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
Third variable effect refers to the effect from a third variable that explains an observed relationship between an exposure and an outcome. Depending on whether there is causal relationship, typically, a third variable takes the format of a mediator or a confounder. A moderation effect is a special case of the third-variable effect, where the moderator and other variables have an interactive effect on the outcome. In this paper, we extend the R package ‘mma’ for moderation analysis so that third-variable effects can be reported at different levels of the moderator. The proposed moderation analysis use tree-structured models to automatically detect moderation effects and can handle both categorical and numerical moderators. We propose algorithms and graphical methods for making inference on moderation effects and illustrate the method under different scenarios of moderation effects. Finally, we apply the proposed method to explore the trend of racial disparities in the use of Oncotype DX recurrence tests among breast cancer patients. We found that the unexplained racial differences in using the tests have decreased from 2010 to 2015.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.16528947.v1（source: https://tandf.figshare.com/articles/dataset/Inference_on_moderation_effect_with_third-variable_effect_analysis_application_to_explore_the_trend_of_racial_disparity_in_oncotype_dx_test_for_breast_cancer_treatment/16528947）。
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