在固定效应模型中缺少依赖变量
1Department of Economics, The University of Texas at Austin, 2225 Speedway Stop C3100, Austin, TX 78712, United States.
概括
本研究引入了对缺少数据的线性固定效应模型的经典最小距离 (CMD) 估计器. 这种方法通过利用所有共变量信息来提高效率,即使缺少依赖变量.
科学领域:
- 计量经济学 计量经济学
- 统计 统计 统计 统计
背景情况:
- 线性固定效应模型被广泛使用,但在缺少数据时可能具有挑战性.
- 传统方法可能会因缺少依赖变量而失去效率.
研究的目的:
- 为缺乏依赖变量的线性固定效应模型提出一种新的估计方法.
- 通过利用所有可用的共变量数据来提高估计效率.
主要方法:
- 一个经典的最小距离 (CMD) 估计器,建立在钱伯林的工作,是开发的.
- 在失踪随机 (MAR) 假设下,估计器被证明是一致的.
- 该方法扩展到自回归固定效应模型,其依赖变量具有滞后性.
主要成果:
- 与完整数据方法相比,CMD估计器提供了效率提升.
- 在某些情况下,即使没有"内部"变化,也可以识别模型参数.
- 蒙特卡洛模拟证明了CMD方法的性能与现有方法相比.
结论:
- 对于缺少数据的固定效应模型,CMD估计器提供了强大而高效的解决方案.
- 该方法适用于静态和动态 (自回归) 模型.
- 进一步的扩展解决了顺序异质性和缺失的共变量.
相关概念视频
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
Truncation in Survival Analysis
209
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...
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...
209
Friedman Two-way Analysis of Variance by Ranks
198
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...
198
Assumptions of Survival Analysis
131
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
131
Clearance Models: Noncompartmental Models
60
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
60
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


