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相关概念视频

z Scores and Unusual Values01:07

z Scores and Unusual Values

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The z score is one of the three measures of relative standing. It describes the location of a value in a dataset relative to the mean. z scores are obtained after the standardization of the values in a dataset. The z score for the mean is 0.
 This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data...
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An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
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Body:Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
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Randomized Experiments01:13

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Introduction to z Scores01:05

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A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
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Introduction to z Scores01:06

Introduction to z Scores

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A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
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常见人的设计在分数等级:蒙特卡洛调查.

Jiayi Liu1, Zhehan Jiang1,2, Tianpeng Zheng1,2

  • 1Peking University, Beijing, China.

Educational and psychological measurement
|November 3, 2025
PubMed
概括

常见人 (CP) 等同提供了高安全性测试的好处. 至少有30个CP,样品特征对准确度的影响最小,使得难度等测试因素转移为等同精度的主要关注点.

关键词:
在IRT真实分数等级等级中,IRT真实分数等级等级.蒙特卡洛模拟的蒙特卡洛模拟常见人的设计是普通人的设计.相当于等于等同的等于等同的等同线性等价法是指线性等价法.评分均等分数使得得分数达到等级.

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科学领域:

  • 心理测量 心理测量 心理测量
  • 教育测量教育的测量
  • 统计建模 统计建模

背景情况:

  • 普通人 (CP) 等同为高安全性测试提供了优势,通过减轻点项目风险和适应非等价组.
  • 关于CP特征如何影响等值准确性的研究有限,实施准则很少.

研究的目的:

  • 系统地检查CP特征和测试设计因素对等准确度的影响.
  • 提供基于证据的指导方针,用于在高风险的测试环境中实施CP等级.

主要方法:

  • 一个全面的蒙特卡洛模拟,每个表格有5000名考生和500个复制.
  • 操纵8个因素,包括测试长度,难度转移,能力分散和测试形式之间的相关性.
  • 使用规范化的RMSE和%Bias.比较四种等同方法 (身份,IRT真得分,线性,等效)

主要成果:

  • 至少30个CP的CP样本大小将样本属性的对等准确性的影响降到最低.
  • 测试难度的变化显著降低了IRT精度,而较长的测试和更广泛的能力分散提高了精度.
  • 当测试形式不同时,线性和等效等效方法显示出优越的稳定性.

结论:

  • 至少有30个CP覆盖得分范围是足以准确等同.
  • 测试因素,特别是难度转移,是等同准确性的关键决定因素.
  • 该研究提供了一个框架,用于平衡使用CP设计的高风险等级中的安全性和准确性.