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相关概念视频

Truncation in Survival Analysis01:09

Truncation in Survival Analysis

122
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...
122
Survival Tree01:19

Survival Tree

37
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
37
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

263
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...
263
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.2K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.2K
Multiple Regression01:25

Multiple Regression

2.8K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
2.8K
Response Surface Methodology01:16

Response Surface Methodology

61
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:
61

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相关实验视频

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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使用二进制响应数据的多变量截断分线进行非参数回归估计.

Afiqah Saffa Suriaslan1, I Nyoman Budiantara1, Vita Ratnasari1

  • 1Department of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Kampus ITS- Sukolilo, Surabaya 60111, Indonesia.

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PubMed
概括
此摘要是机器生成的。

这项研究引入了对二进制数据的新型Truncated Spline非参数回归模型,为复杂关系提供比传统的二进制逻辑回归更准确的预测.

关键词:
二进制响应数据二进制响应数据非参数回归的非参数回归截断的线 截断的线

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科学领域:

  • 统计 统计 统计 统计
  • 计量经济学 计量经济学

背景情况:

  • 传统的截断分线估计器是用于定量数据的,限制了它们的使用与二进制结果.
  • 二元响应变量在现实应用中很常见,需要专门的回归模型.

研究的目的:

  • 为二进制响应数据开发一个多变量截断分线非参数回归估计器.
  • 解决对模型的需求,这些模型可以在特定的子区间中捕捉变化的变量关系,用于二进制结果.

主要方法:

  • 为二进制数据提出了一种新的多变量截断分线非参数回归估计器.
  • 使用Akaike信息标准 (AIC) 进行最佳结点选择.
  • 将估计器应用于有关公共卫生和社会经济指标的现实数据集.

主要成果:

  • 与二进制物流回归相比,截断断线非参数回归方法的准确性更高.
  • 该模型有效地处理对二进制响应的子间隔的变化模式的关系.
  • 在模型中,AIC为选择最佳结点提供了一个有效的标准.

结论:

  • 开发的Truncated Spline估计器是分析具有复杂关系的二进制响应数据的宝贵工具.
  • 这种方法比标准的二进制逻辑回归提供了更好的估计准确性.
  • 该方法适用于需要对二进制结果进行非参数分析的各种领域.