MRSA感染逻辑回归模型数据集
包含两个逻辑回归模型数据,用于识别MRSA感染的风险因素,涉及人口学、保险状态等变量,样本量分别为184和455。

基本信息
资源简介
MRSA感染逻辑回归模型数据集
【数据集背景】
本数据集源站标题为《(a) Logistic regression Model 1. including variables demonstrating significant association with MRSA infection on bivariate analysis (n = 184); (b) Logistic regression Model 2. same as Model 1. excluding variable for ever been incarcerated (n = 455).》。源站首次发布:2013-02-20。
【数据内容】
源站原始描述:*African American (n = 139) compared with all others of known race (n = 45). †Public Insurance or uninsured (n = 131) compared with privately insured (n = 53). ‡Indicates odds ratio for every additional person in the household. ∫African American (n = 353) compared with all others of known race (n = 102). ¶Public Insurance or uninsured (n = 333) compared with privately insured (n = 122). Abbreviations: SSTI, skin or soft tissue infection
【数据结构与技术规格】
文件数 1 个,合计 9.73 KB。Table_5.xls:application/vnd.ms-excel,9.73 KB。数据集 DOI:10.1371/journal.pone.0018217.t005。
【主题与分类】
源站学科分类:Microbiology、Genetics、Infectious Diseases、Biotechnology。主题标签:logistic、regression、variables、demonstrating、mrsa、bivariate、been、incarcerated。
【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://plos.figshare.com/articles/dataset/_a_Logistic_regression_Model_1_including_variables_demonstrating_significant_association_with_MRSA_infection_on_bivariate_analysis_n_184_b_Logistic_regression_Model_2_same_as_Model_1_excluding_variable_for_ever_been_incarcerated_n_455_/453726
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Z. David, Michael; Boyle-Vavra, Susan; L. Zychowski, Diana; S. Daum, Robert (2015). (a) Logistic regression Model 1. including variables demonstrating significant association with MRSA infection on bivariate analysis (n = 184); (b) Logistic regression Model 2. same as Model 1. excluding variable for…
【使用注意】
· 源站最后修改于 2023-05-31,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。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放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:(a) Logistic regression Model 1. including variables demonstrating significant association with MRSA infection on bivariate analysis (<i>n</i> = 184); (b) Logistic regression Model 2. same as Model 1. <i>excluding</i> variable for ever been incarcerated (<i>n</i> = 455).
- DOI:10.1371/journal.pone.0018217.t005
- 发布日期:2013-02-20
- 文件数:1 个
- 文件总体积:9.73 KB
- 源站页面:https://plos.figshare.com/articles/dataset/_a_Logistic_regression_Model_1_including_variables_demonstrating_significant_association_with_MRSA_infection_on_bivariate_analysis_n_184_b_Logistic_regression_Model_2_same_as_Model_1_excluding_variable_for_ever_been_incarcerated_n_455_/453726
命令行下载
curl -L -o "Table_5.xls" "https://ndownloader.figshare.com/files/783366"
文件清单
Table_5.xls(9.73 KB)
文件总体积 9.73 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
*African American (n = 139) compared with all others of known race (n = 45).
†Public Insurance or uninsured (n = 131) compared with privately insured (n = 53).
‡Indicates odds ratio for every additional person in the household.
∫African American (n = 353) compared with all others of known race (n = 102).
¶Public Insurance or uninsured (n = 333) compared with privately insured (n = 122).
Abbreviations: SSTI, skin or soft tissue infection.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0018217.t005(source: https://plos.figshare.com/articles/dataset/_a_Logistic_regression_Model_1_including_variables_demonstrating_significant_association_with_MRSA_infection_on_bivariate_analysis_n_184_b_Logistic_regression_Model_2_same_as_Model_1_excluding_variable_for_ever_been_incarcerated_n_455_/453726)。
数据缺失?
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