相关实验视频

Updated: Sep 12, 2025

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers
09:16

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers

Published on: March 14, 2018

10.3K

解决视觉模拟尺度中的报告异质性:使用 anchoring vignettes 的双指数模型方法

Zhiyong Huang1, Fabrice Kämpfen2

  • 1SouthWestern University of Finance and Economics, Chengdu, China.

Health and quality of life outcomes
|August 10, 2025
PubMed
概括

在视觉模拟尺度 (VAS) 中报告异质性可能会扭曲结果. 本研究介绍了使用基于VAS的 anchoring vignettes来纠正这种偏差的方法,可能会改变以前关于生活质量 (QoL) 和性别的发现.

关键词:
方法 方法 方法 方法生活质量生活的质量.报告异质性的报告.视觉模拟尺度是一个可视模拟尺度.

更多相关视频

A Two-interval Forced-choice Task for Multisensory Comparisons07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

11.0K
Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.4K

相关概念视频

The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.4K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
296
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
25.7K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.9K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.5K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
155