量化趋势的趋势性趋势的量化
Andreas Kryger Jensen1, Claus Thorn Ekstrøm1
1Biostatistics, Institute of Public Health University of Copenhagen, Copenhagen, Denmark.
概括
量化公共卫生数据的趋势性至关重要. 新的指数,趋势方向指数和预期趋势不稳定性,衡量趋势的变化,帮助分析吸烟率和COVID-19病例等健康结果.
科学领域:
- 统计 统计 统计 统计
- 流行病学 流行病学
- 公共卫生 公共卫生
背景情况:
- 新闻媒体经常根据纵向数据报告公共卫生趋势的变化.
- 这些报告的趋势变化,通常发生在最近的数据点,可以影响国家公共卫生决策.
研究的目的:
- 提出新的统计措施来量化公共卫生数据趋势的"趋势性".
- 引入一个概率趋势方向指数和一个预期趋势不稳定性指数.
主要方法:
- 在连续时间内定义趋势和趋势变化.
- 开发一个概率趋势方向指数 (单调性变化的概率).
- 定义预期趋势的不稳定性指数 (预期的趋势变化数量).
- 在贝叶斯框架内利用潜在的高斯过程模型进行估计.
主要成果:
- 证明了趋势方向指数和预期趋势不稳定性的估计.
- 应用了分析20年来丹麦吸烟比例的方法.
- 分析了从2月24日起意大利新增COVID-19病例的发展情况.
结论:
- 拟议的指数提供了一种定量方法来评估公共卫生数据的趋势变化.
- 这些方法为分析复杂的健康动态和为公共卫生战略提供信息提供了有价值的工具.
相关概念视频
Time-Series Graph
4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.4K
Central Tendency: Analysis
175
Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
175
Regression Toward the Mean
6.3K
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...
6.3K
Trends in Lattice Energy: Ion Size and Charge
24.0K
An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
24.0K
Measures of Central Tendency
16.0K
The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians,...
16.0K
Residuals and Least-Squares Property
7.5K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.5K


