在元分析的多变量随机效应模型下,研究间协差矩阵的多步估计器
Dan Jackson1, Wolfgang Viechtbauer2, Robbie C M van Aert3
1Statistical Innovation, AstraZeneca, Cambridge, UK.
Statistics in medicine
|December 19, 2023
概括
在元分析中,用于研究间协差矩阵的新型多变量多步估计器提供了一个可行的替代方案,特别是在异质数据中. 这些方法在计算上是可行的,并且适合于元回归.
科学领域:
- 统计 统计 统计 统计
- 生物统计学 生物统计学
- 流行病学 流行病学
背景情况:
- 估计研究间的差异对于随机效应的元分析至关重要.
- 现有的多变量估计器是单变量方法的有限扩展.
研究的目的:
- 开发用于研究间协差矩阵的新型多变量估计器.
- 为了将瞬间的概括方法扩展到多变量设置.
主要方法:
- 延伸到单变量普遍的时刻方法.
- 多变量多步估计器的推导.
- 随着步骤接近无限,研究多步估计器的极限.
主要成果:
- 拟议的方法是现有方法的可行替代方案.
- 多步估计器在异质数据方面表现良好,但在同质数据方面表现不佳.
- 新的估计器是半参数的,在高维度中计算可行.
结论:
- 提出的多变量多步估计器是对元分析的完全可行的替代方案.
- 这些方法非常适合用于敏感性分析和异质数据.
- 适用于多变量随机效应元回归.
相关概念视频
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
515
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...
On...
515
Friedman Two-way Analysis of Variance by Ranks
200
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
200
Multiple Regression
3.0K
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...
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...
3.0K
Mechanistic Models: Compartment Models in Individual and Population Analysis
43
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...
43
Statistical Methods to Analyze Parametric Data: ANOVA
382
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
382
Estimating Population Mean with Unknown Standard Deviation
7.7K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
William S. Gosset (1876–1937) of the...
7.7K


