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二级自回归(AR(1))模型中的解释方差与组内相关

Explained Variance and Intraclass Correlation in a Two-Level AR(1) Model.

作者信息

Jongerling J, Hoijtink H

机构信息

a Department of Psychology, Education, and Child Studies, Faculty of Social Sciences , Eramus University.

b Department of Methodology and Statistics, Faculty of Social and Behavioral Sciences , Utrecht University.

出版信息

Multivariate Behav Res. 2017 Jul-Aug;52(4):403-415. doi: 10.1080/00273171.2017.1299616. Epub 2017 Apr 4.

Abstract

The total variance of a first-order autoregressive AR(1) time series is well known in time series literature. However, despite the increased use and interest in two-level AR(1) models, an equation for the total variance of these models does not exist. This paper presents an approximation of this total variance. It will be used to compute the unexplained and explained variance at each level of the model, the proportion of explained variance, and the intraclass correlation (ICC). The use of these variances and the ICC will be illustrated using an example concerning structured diary data about the positive affect of 96 married women.

摘要

一阶自回归AR(1)时间序列的总方差在时间序列文献中是众所周知的。然而,尽管二级AR(1)模型的使用和关注度有所增加,但这些模型的总方差方程并不存在。本文提出了该总方差的一个近似值。它将用于计算模型各层级的未解释方差和解释方差、解释方差的比例以及组内相关系数(ICC)。将通过一个关于96名已婚女性积极情绪的结构化日记数据的例子来说明这些方差和ICC的用途。

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