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相关概念视频

Kaplan-Meier Approach01:24

Kaplan-Meier Approach

149
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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What are Estimates?01:06

What are Estimates?

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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
5.0K
Censoring Survival Data01:09

Censoring Survival Data

97
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
97
Hazard Rate01:11

Hazard Rate

112
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
112
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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相关实验视频

Updated: Jul 7, 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

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对计数和反复事件数据的边际与条件率估计,使用估计和框架.

Sarah C Conner1, Yijie Zhou1, Tu Xu2

  • 1Vertex Pharmaceuticals, 50 Northern Ave, Boston, MA 02210, USA.

Contemporary clinical trials
|December 23, 2023
PubMed
概括

在临床研究中,模型估计的事件率,特别是COPD或喘中的肺恶化 (PEx),可能因条件与边际速率的区别而不同于描述速率. 非线性模型中的共变量调整会影响这些估计,与最近的FDA指南保持一致.

科学领域:

  • 临床试验 临床试验
  • 生物统计学 生物统计学
  • 流行病学 流行病学

背景情况:

  • 在临床研究中,计数和复发事件终点对于评估治疗疗效至关重要.
  • 在COPD和喘等疾病中,肺部恶化 (PEx) 是使用非线性模型 (例如Poisson,负二项式) 分析的常见复发事件.
  • 在模型估计的集团内部事件率低于描述性率时,经常会观察到差异.

研究的目的:

  • 在数学上探索模型估计和描述事件速率之间的关系.
  • 阐明共变量调整对非线性模型中事件率和速率比率估计的影响.
  • 讨论对计数和反复事件数据的估计和框架的应用.

主要方法:

  • 数学分析以区分条件和人口级 (边际) 事件率.
  • 封闭式导数和模拟研究,以证明共变量调整的影响.
  • 审查和讨论关于估计和框架的ICH E9附录.

主要成果:

  • 模型估计和描述性利率之间的观察到的差异是由条件和边际利率之间的区别数学解释的.
  • 与未经调整的模型相比,非线性模型中的共变量调整可能导致事件率和速率比率的估计不同.
  • 这些发现支持FDA在非线性模型中对共变量调整的2023年指导.
关键词:
崩性 崩性 崩性预计和框架 预计和框架这就是G计算.一般化的线性模型.边际/有条件利率 边际/有条件利率经常发生的事件.

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结论:

  • 了解条件和边际率之间的差异对于准确解释临床试验结果至关重要.
  • 同变量调整策略需要在反复事件的非线性模型中仔细考虑,影响治疗效果估计.
  • 估计框架提供了一个结构化的方法,用于定义和估计复杂的临床试验设计中的治疗效果.