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Differential Leveling01:12

Differential Leveling

170
Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
170
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

3.3K
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...
3.3K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

5.8K
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:
5.8K
Ratio Level of Measurement00:54

Ratio Level of Measurement

17.8K
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.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
17.8K
Data Validation01:15

Data Validation

161
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
161
Multiple Comparison Tests01:13

Multiple Comparison Tests

3.9K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
3.9K

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Updated: Jun 26, 2025

A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing
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A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing

Published on: February 7, 2025

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评估不同级别的形状差异等同方法.

Ting Sun1, Stella Yun Kim2

  • 1University of Utah, Salt Lake City, USA.

Educational and psychological measurement
|May 17, 2024
PubMed
概括
此摘要是机器生成的。

选择正确的统计等同方法取决于不同测试形式的困难程度. 这项研究指导了从业人员选择适当的等分技术,以准确解释分数.

关键词:
在等同化方面,它是相当的.困难形式 困难形式

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Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
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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:

  • 为测试形式的难度差异进行等级调整,以确保可比得分.
  • 当前的等式化实践往往忽视了形式难度变化的程度.
  • 缺乏指导,以选择基于形式难度差异的等式化方法.

研究的目的:

  • 调查不同形式的难度差异对等准确度的影响.
  • 在不同的难度场景下,比较不同等级方法在不同难度场景下的性能.
  • 提供以证据为基础的建议,用于等价方法的选择.

主要方法:

  • 模拟研究评估六种等价方法.
  • 研究了两种常见的等同设计:随机组 (RG) 和常见项目无等价组 (CINEG).
  • 条件包括不同级别的形式难度差异,从没有到很大.

主要成果:

  • 在RG设计中,平均等值在没有/小差异的情况下表现出色;对中等/大差异而言,平均等值优越.
  • 对于CINEG设计,Tucker Linear在小/中差异方面表现最好;链式等比值或频率估计在大差异方面是最佳的.
  • 方程式方法的性能受到形式难度差异的大小的显著影响.

结论:

  • 这项研究为根据形式难度选择合适的等分方法提供了关键指导.
  • 结果为测试公司提供了相似和不相似的测试形式的最佳等同策略的信息.
  • 准确的得分可比性依赖于将等分方法与形式难度差异的程度相匹配.