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相关概念视频

Response Surface Methodology01:16

Response Surface Methodology

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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:
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Modeling in Therapy01:26

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Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
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Self-Report Tests of Personality

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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.
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People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about...
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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...
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相关实验视频

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"如果申请人伪造他们的答案呢? ":在高风险评估中模拟伪造和响应风格,使用多维名义响应模型.

Timo Seitz1, Maik Spengler2, Thorsten Meiser1

  • 1University of Mannheim, Germany.

Educational and psychological measurement
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PubMed
概括

本研究引入了一种扩展的多维名义响应模型 (MNRM),用于检测和纠正高风险评估中伪造的人格测试的情况. 该模型通过考虑响应偏差来提高测量特征的准确性.

关键词:
假装是假的 假装是假的高风险评估高风险评估多维物品响应理论是多维物品反应理论.标称响应模型的名义响应模型在社会上是可取的响应反应.

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科学领域:

  • 心理测量 心理测量
  • 心理测量 心理测量 心理测量
  • 人格评估 个性评估

背景情况:

  • 自我报告人格测试容易被伪造,特别是在高风险的情况下,如求职申请.
  • 现有的模型可能无法完全捕捉响应偏差的项目特定性质.
  • 准确的人格评估对于公平有效的决策至关重要.

研究的目的:

  • 将多维名义响应模型 (MNRM) 扩展到明确模拟和解释人格评估中的伪造行为.
  • 在模拟研究和现实世界高风险测试场景中评估扩展的MNRM的性能.
  • 证明模型在提高人格特征得分的准确性和有效性方面的实用性.

主要方法:

  • 开发了多维名义响应模型 (MNRM) 的扩展,其中包含了伪造维度.
  • 进行模拟研究以评估参数恢复和模型选择性能.
  • 将扩展的MNRM应用于高风险环境中的3046名求职者和低风险环境中的现有职位的数据.
  • 使用了从试点研究中得出的特定项目评分权重来模拟模拟效应.

主要成果:

  • 扩展的MNRM在模拟中显示了良好的参数恢复.
  • 与没有伪造的模型相比,模拟伪造显著改善了模型适合性和差异有效性.
  • 假装维度显示了与共变量有意义的关系.
  • 该模型有效地捕捉了假冒,并在高风险和低风险条件下调整了特征得分.

结论:

  • 扩展的MNRM提供了一种可靠的方法来检测和纠正人格评估中的伪造.
  • 对伪造的记账增强了人格指标的心理测量属性和有效性.
  • 这种方法对提高高风险评估环境的完整性有重大影响.