一个相对规范的效果大小差异指数,用于确定探索性解决方案中共同因素的数量
Pere J Ferrando1, David Navarro-González1, Urbano Lorenzo-Seva1
1Universitat Rovira i Virgili, Tarragona, Spain.
Educational and psychological measurement
|July 26, 2024
概括
本研究引入了一种新的相对差异指数,通过评估常见因子方差来改进探索性因子分析 (EFA). 这提高了对项目分析中的因素数量的决策能力.
科学领域:
- 心理测量 心理测量 心理测量
- 统计 统计 统计 统计
- 数据分析 数据分析
背景情况:
- 描述性合适指数有助于评估不受限制的或探索性的因子分析 (UFA) 解决方案,特别是用于确定共同因子的数量.
- 虽然总体指数在UFA中很常见,特别是在项目分析中,但差异指数不那么普遍.
- 雷科夫和合作者为UFA引入了有希望的效果大小类型描述差异指数.
研究的目的:
- 提出雷科夫效应大小测量的相对版本,作为对原始绝对测量的补充.
- 通过模拟在项目分析环境中为两个指数建立参考值.
- 在R和非商业因素分析程序中实施拟议的指数.
主要方法:
- 发展一种相对差异指数,将解释的共同方差与先前的共同因子方差联系起来.
- 模拟研究以确定项目分析场景中拟议和原始指数的参考值.
- 在R和广泛使用的非商业因素分析软件中实施指数.
主要成果:
- 提出并实施了一种新的相对差异指数.
- 绝对指数和相对指数的参考值是通过模拟建立的,用于项目分析.
- 通过使用经验数据集证明了拟议的指数的实际实用性.
结论:
- 提出的相对差异指数是对评估UFA解决方案的现有措施的有价值补充.
- 建立的参考值为在项目分析中应用这些指数提供了实际指导.
- 在R和其他软件中的实现有助于采用这些新的描述性适合性指数.
相关概念视频
Identifying Statistically Significant Differences: The F-Test
1.6K
The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...
1.6K
Factorial Design
13.0K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.0K
Friedman Two-way Analysis of Variance by Ranks
177
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...
177
One-Way ANOVA: Unequal Sample Sizes
5.7K
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:
5.7K
Compacting Factor test
128
The compacting factor test is a method used to assess the workability of concrete. It is especially suitable for concrete mixes containing aggregates up to one and a half inches in size. This test involves specialized equipment consisting of two truncated cone-shaped hoppers and a cylinder, all with polished interior surfaces to minimize friction.
The procedure begins by placing concrete into the upper hopper without any compaction. Once filled, the bottom door of this hopper is opened,...
The procedure begins by placing concrete into the upper hopper without any compaction. Once filled, the bottom door of this hopper is opened,...
128
Bonferroni Test
2.7K
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
2.7K


