A predictive approach to the random effect model

SEYMOUR GEISSER

doi:10.1093/biomet/61.1.101

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A predictive approach to the random effect model

SEYMOUR GEISSER刊期 1974 · 卷 61（1）Biometrika已编入正刊

随机效应模型的预测方法AI 解读 ↓

一般估计

被引 2,658 次 ↗OpenAlex · 核验 2026-10-04

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DOI · 10.1093/biomet/61.1.101

Biometrika · 卷 61，期 1 · 页码 / 文章号 101-107

正式刊期日期：1974

DOI 首次登记：2007-01-04

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SEYMOUR GEISSER

AI 解读 · 基于可核验材料

随机效应模型的预测方法

研究问题: 如何利用预测性样本重用估计随机效应模型中的均值，并将所得估计量与已有方法在实际数据上进行比较？
方法与思路: 作者通过预测性样本重用导出两个简单的均值估计量，应用于文献中的两组数据，与其他程序比较，并讨论混合模型。
材料陈述的贡献: 摘要明确报告了两个估计量的推导及两组数据应用，同时涉及混合模型；没有说明比较所得的优势或理论性质。
阅读关注点: 应核对预测性样本重用的操作方式、均值估计目标和随机效应设定，以及比较采用的损失准则与混合模型扩展。
阅读边界: 来源为版本未注明的 OpenAlex 索引摘要；未说明数据结构、估计公式或比较结果，不能据随机效应推断其属于面板研究。

GPT-6.1 Sol · 高 · 2026-10-05

原文摘要

Two simple estimators are derived here for the means of the random effect model by means of predictive sample reuse. They are applied to two sets of data in the literature and compared with several other procedures. The mixed model is also discussed.

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