Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

343
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
343
Binomial Probability Distribution01:15

Binomial Probability Distribution

10.2K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.2K
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

151
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
151
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

26
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
26
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

296
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
296
Statistical Package for the Social Sciences (SPSS)01:22

Statistical Package for the Social Sciences (SPSS)

249
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
249

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A construction of statistical inferences in geographically weighted univariate log-gamma regression.

MethodsX·2026
Same author

Confidence interval construction for multivariable truncated spline logistic model (MTSLM).

MethodsX·2026
Same author

A multivariate correlated poisson generalized inverse gaussian regression model for dependent count data: Estimation and testing procedures.

MethodsX·2026
Same author

A statistical inference framework for FSNBLR: Modeling underdeveloped regional status in Eastern Indonesia.

MethodsX·2026
Same author

Geographically weighted Weibull regression modeling on dissolved oxygen data to analyze river water quality in East Kalimantan.

MethodsX·2026
Same author

Statistical inferences and applications of nonparametric regression models based on fourier series.

MethodsX·2025

相关实验视频

Updated: Jun 2, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K

通过统计建模探索贫困:双变多项二进制逻辑回归 (BPBLR)

Vita Ratnasari1, Purhadi1, Marisa Rifada1

  • 1Sepuluh Nopember Institute of Technology, Airlangga University, Mulawarman University, Indonesia.

MethodsX
|January 15, 2025
PubMed
概括
此摘要是机器生成的。

我们介绍了双变多项二进制逻辑回归 (BPBLR) 用于分析两个相关的二进制结果. 这种统计方法增强了对复杂的分类数据分析的逻辑回归,有助于评估贫困.

关键词:
二进制响应二进制响应双变的 双变的逻辑回归的逻辑回归方法多项式是一个多项式.贫困 贫困 贫困 贫困 贫困双变的多项式逻辑回归模型

更多相关视频

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.3K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.6K

相关实验视频

Last Updated: Jun 2, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.3K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.6K

科学领域:

  • 统计 统计 统计 统计
  • 计量经济学 计量经济学
  • 社会科学 社会科学 社会科学

背景情况:

  • 逻辑回归是一种用于分析分类数据,特别是二进制响应的标准统计方法.
  • 现有的模型往往难以有效地捕捉多个二进制结果变量之间的相关性.

研究的目的:

  • 为了引入双变多项二进制逻辑回归 (BPBLR) 模型.
  • 使用多项式模式扩展逻辑回归来建模两个相关的二进制响应变量.
  • 将BPBLR模型应用于可持续发展目标 (SDGs) 的现实世界贫困数据 1.

主要方法:

  • 提出了双变多项二进制逻辑回归 (BPBLR) 模型,它结合了多项式模式来描述相关的二进制响应和预测变量之间的关联.
  • 参数估计是使用最大概率估计 (MLE) 方法进行的.
  • 该模型的统计测试是使用最大概率比率测试 (MLRT) 进行的,测试统计数据以非对称的方式遵循基平方分布.
  • 模型选择和最佳多项式度的确定是基于最小化偏差值.

主要成果:

  • 该BPBLR模型提供了一种新的方法,用于对类别数据的统计建模,其中有两个相关的二进制响应变量.
  • 使用MLRT方法对拟议模型进行可靠的统计测试.
  • 对贫困数据集的应用证明了该模型在分析贫困的深度和严重程度方面的实用性,有助于实现可持续发展目标1的目标.

结论:

  • 该BPBLR模型为处理相关的二进制结果提供了一个重要的统计建模创新.
  • 开发的方法,包括MLE和MLRT,为分析和测试提供了一个全面的框架.
  • 对贫困数据的成功应用凸显了该模型在解决复杂的社会问题和支持全球发展目标方面的实际相关性.