如何理解可靠性?如何理解可靠性? 常用语言解释可靠性和可靠性与效果大小的关系
Jari Metsämuuronen1, Timi Niemensivu1
1Faculty of Science, Turku Research Institute for Learning Analytics, University of Turku, Turku, Finland.
Applied psychological measurement
|June 27, 2025
概括
沟通可靠性估计是一个挑战. 本研究引入了通缩校正可靠性估计 (DCER) 以将可靠性得分转化为通用语言效果大小,帮助解释和大小评估.
科学领域:
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
- 教育测量教育的测量
背景情况:
- 在普通语言中解释特定的可靠性估计 (例如,0.80,0.95) 通常是困难的.
- 传统的可靠性估计对于非专家来说缺乏直观的意义.
- 需要一个指标,使可靠性与可理解的效果大小解释保持一致.
研究的目的:
- 将通缩调整后可靠性估计 (DCER) 转换为通用语言效果大小.
- 为了使可靠性估计的沟通使用日常语言.
- 为了评估可靠性估计的大小,使用与效果大小相同的指标.
主要方法:
- 使用Somers' D或Goodman-Kruskal G作为DCER计算的项目得分相关性.
- 将DCER转换为通用语言效果大小表单.
- 为可靠性大小的实际解释提供值.
主要成果:
- DCER允许以正确对排序的概率来表达可靠性估计.
- 用40个项目的可靠性为0.95,表明在80%的随机对中,更高的项目响应与更高的测试分数相关.
- 可靠性大小可以使用熟悉的效果大小值 (例如",非常高") 来分类.
结论:
- DCER提供了一种直观且易于使用的方法,用于理解和传达测试可靠性.
- 这种方法弥合了统计可靠性指标和实际解释之间的差距.
- 这种转换有助于更有意义地评估各种领域的测量精度.
更多相关视频
05:51Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
Published on: February 21, 2025
678
06:17A Task for Assessing the Impact of a Partner on the Speed and Accuracy of Motor Performance in Rats
Published on: October 17, 2019
5.0K
相关概念视频
Reliability and Validity
13.2K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.2K
Statistical Significance
20.4K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
20.4K
Interpretation of Confidence Intervals
6.6K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
6.6K
Statistical Analysis: Overview
7.5K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
7.5K
Odds Ratio
272
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
272
Relative Risk
361
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
361
