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相关概念视频

Introduction to Test of Independence01:21

Introduction to Test of Independence

2.2K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
2.2K
Hypothesis Test for Test of Independence01:16

Hypothesis Test for Test of Independence

3.6K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
3.6K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

2.5K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
2.5K
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test01:09

Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test

1.6K
In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
1.6K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

177
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
177
Contingency Table01:29

Contingency Table

2.5K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.5K

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相关实验视频

Updated: Jun 26, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.2K

测试具有功能共变量的条件量子独立性.

Yongzhen Feng1, Jie Li2, Xiaojun Song3

  • 1Center for Statistical Science and Department of Industrial Engineering, Tsinghua University, Beijing 100084, China.

Biometrics
|May 14, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了功能数据的新型非参数条件独立性测试,有效地解决了维度的诅咒. 拟议的方法在检测依赖关系方面表现出强大的力量,通过模拟和EEG数据分析进行验证.

关键词:
实证过程是经验过程.功能数据 功能数据多倍器启动链.量子的独立性 量子的独立性随机投影是随机的投影.

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An R-Based Landscape Validation of a Competing Risk Model
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An R-Based Landscape Validation of a Competing Risk Model

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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

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相关实验视频

Last Updated: Jun 26, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

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An R-Based Landscape Validation of a Competing Risk Model
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An R-Based Landscape Validation of a Competing Risk Model

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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

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科学领域:

  • 统计 统计 统计 统计
  • 功能数据分析 功能数据分析
  • 非参数统计的统计数据.

背景情况:

  • 条件独立性测试在统计建模中至关重要.
  • 现有的方法经常与高维的功能共变量作斗争.
  • 维度的诅咒在功能数据分析中构成了重大挑战.

研究的目的:

  • 开发一种新的非参数条件独立性测试,用于标量响应和功能共变量.
  • 在功能数据分析中解决维度的诅咒.
  • 为分析复杂数据集提供多功能统计工具.

主要方法:

  • 克拉默--米塞斯类型测试统计数据是使用经验过程构建的.
  • 为了减轻维度性,使用函数共变量的随机投影.
  • 非对称的零分布和功率属性是在温和假设下得出的.
  • 建议用于临界值估计的乘数引导.

主要成果:

  • 提出的测试有效地避免了零假设下的维度的诅咒.
  • 测试统计显示了可取的非对称的全球和局部功率属性.
  • 它可以检测到以参数速率收的局部替代品.
  • 蒙特卡洛模拟证实了有限样本的良好性能.

结论:

  • 开发的非参数测试为使用功能共变量进行条件独立性测试提供了强大且计算效率高的解决方案.
  • 通过对EEG数据的实际应用来证明该方法的实用性.
  • 这种方法在使用功能数据的领域中增强了统计推理.