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相关概念视频

Censoring Survival Data01:09

Censoring Survival Data

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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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Archival Research01:40

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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
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Statistical Methods for Analyzing Epidemiological Data01:25

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Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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更好的数据,更少的枪支暴力

Andrew R Morral1, Rosanna Smart2

  • 1Andrew R. Morral is a senior behavioral scientist, director of the National Collaborative on Gun Violence Research, and director of the RAND Gun Policy in America Initiative at the RAND Corporation, Washington, DC, USA.

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概括
此摘要是机器生成的。

在经历了数十年的资金不足之后, 枪支暴力预防研究的资金从私人和公共来源大幅增加. 这一激增旨在更好地应对美国枪支暴力的规模.

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科学领域:

  • 公共卫生
  • 犯罪学
  • 卫生政策

背景情况:

  • 联邦政府对枪支暴力预防研究的有限资金持续了25年.
  • 尽管有专注的努力, 研究的规模并没有与枪支暴力的公共卫生问题相匹配.
  • 近年来,该研究领域的投资大幅增加.

研究的目的:

  • 突出枪支暴力预防研究的历史性资金不足.
  • 记录最近来自不同来源的研究资金激增.
  • 强调人们越来越认识到对枪支暴力的依据性解决方案的必要性.

主要方法:

  • 对枪支暴力预防研究的历史资助趋势的分析.
  • 识别和量化来自公共和私营实体的近期融资举措.
  • 审查与枪支暴力造成的公共卫生负担相关的投资规模.

主要成果:

  • 美国政府为预防枪支暴力的研究提供了最低限度的资金.
  • 自2018年以来,研究资金大幅增加,超过2100万美元.
  • 自2019年以来,每年联邦承诺2500万美元,补充了州和慈善投资.

结论:

  • 枪支暴力预防研究领域正在经历前所未有的财政支持增长.
  • 这种增加的投资对于促进科学理解和制定有效的预防策略至关重要.
  • 私人慈善机构,联邦机构和州政府的共同努力,