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相关概念视频

Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Comparing the Survival Analysis of Two or More Groups01:20

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Random Sampling Method01:09

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Censoring Survival Data01:09

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Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
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Sampling Methods: Overview01:06

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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在基于电子健康记录的比较有效性研究中,对信息性缺失的数据进行双采样.

Alexander W Levis1, Rajarshi Mukherjee2, Rui Wang2,3

  • 1Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania.

Statistics in medicine
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PubMed
概括
此摘要是机器生成的。

双采样提供了一个强大的解决方案,用于处理电子健康记录 (EHR) 中缺失的数据,这些数据是不随机缺失的 (MNAR). 这种方法使得可靠的估计和推断的因果关系的影响,即使有复杂的数据问题.

关键词:
有关因果推理的推理.采用双重抽样的方式.缺失的数据 缺失的数据半参数理论 半参数理论研究设计研究设计

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科学领域:

  • 生物统计学 生物统计学
  • 流行病学 流行病学
  • 医疗信息学 医疗信息学

背景情况:

  • 电子健康记录 (EHR) 中缺少数据是常见的,特别是当数据缺失时不是随机的 (MNAR).
  • 目前对MNAR数据的敏感性分析往往缺乏可操作的结论.
  • 腹腔外科手术结果研究经常遇到MNAR数据.

研究的目的:

  • 引入和评估双重抽样作为一种方法来处理在EHR中的MNAR结果数据.
  • 为了能够准确地估计和推断因果关系,尽管缺少数据.
  • 为健康结果研究提供强大的统计工具.

主要方法:

  • 在双重抽样下,开发了用于识别联合分布的假设.
  • 获得了平均因果治疗效果 (ACTE) 的高效和可靠估计器.
  • 通过模拟,通过非参数和随机缺失 (MAR) 模型进行比较估计.

主要成果:

  • 双样采样为使用MNAR数据进行因果推理提供了一个框架.
  • 建议的估计器证明了效率和稳定性.
  • 该方法扩展到处理任意数据粗化机制.

结论:

  • 双样采样是一种可行的策略,可以在EHR研究中减轻MNAR数据.
  • 由此产生的估计器提供了更好的因果效应估计.
  • 这种方法提高了不完整数据的健康研究结果的可靠性.