检查荷兰语中"平衡应答人数清单"第6版的简体形式:在多维框架中比较多元和二元分数方法
Mirthe G C Noteborn1, Martin Hildebrand2,3, Jelle J Sijtsema1,4,5
1Department of Developmental Psychology, Tilburg University, Tilburg, Netherlands.
Frontiers in psychology
|June 30, 2025
概括
一个新的20项荷兰版本的平衡库存的理想的响应 (BIDR-D20) 的开发和验证. 这种较短的尺度保持了与原来的40项BIDR可比的心理测量质量,提供了更有效的时间测量社会可取性.
科学领域:
- 心理测量 心理测量
- 社会心理学 社会心理学
背景情况:
- 值得回应的40项平衡库存 (BIDR) 版本6是评估社会可取性的关键工具,特别是自我欺骗增强 (SDE) 和印象管理 (IM).
- 开发一个更短,经过验证的荷兰版本对于高效和有效的研究在这个领域至关重要.
研究的目的:
- 创建和验证40项BIDR.的荷兰语版本的简体形式.
- 在多项研究中评估新简体形式的心理测量特性和实用性.
主要方法:
- 使用物件响应理论 (IRT) 分析,从一般人口样本中选择简单表格的项目.
- 通过将其与人格特征和偏离行为相关联,检查了简体形式的名学网络.
- 在一个单独的研究中,研究了SDE和IM在自我报告的侵略中检测响应偏差的能力.
主要成果:
- 一个20个项目简单表格 (BIDR-D20) 开发了10个SDE和10个IM项目,使用二分法评分.
- 发现BIDR-D20的心理测量质量与原来的BIDR版本6相等或更好,尽管信息略有丢失.
- 与多元分数相比,二元分数得分显示出优越的模型合适性和内部一致性.
结论:
- BIDR-D20是40项BIDR版本6的潜在有价值和时间高效的替代品.
- 需要进一步的研究才能充分确定BIDR-D20的预测有效性作为响应偏差的衡量标准.
更多相关视频
相关概念视频
Self-Report Tests of Personality
460
Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
460
Ordinal Level of Measurement
25.8K
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...
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...
25.8K
Friedman Two-way Analysis of Variance by Ranks
308
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...
308
McNemar's Test
436
McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...
436
Decision Making: P-value Method
5.7K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.7K
Response Surface Methodology
284
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
284


