Structural Equation Models with Observed Variables

结构方程建模 潜变量 峰度 应用数学 数学 协方差 联立方程模型 最小二乘函数近似 协方差矩阵 鉴定(生物学) 规范 变量(数学) 计量经济学 统计 数学分析 生物 植物 估计员
作者
Kenneth A. Bollen
标识
DOI:10.1002/9781118619179.ch4
摘要

Chapter Four Structural Equation Models with Observed Variables Kenneth A. Bollen, Kenneth A. BollenSearch for more papers by this author Kenneth A. Bollen, Kenneth A. BollenSearch for more papers by this author Kenneth A. Bollen, Kenneth A. Bollen Department of Sociology, the University of North Carolina at Chapel Hill, Chapel Hill, North CarolinaSearch for more papers by this author Book Author(s):Kenneth A. Bollen, Kenneth A. Bollen Department of Sociology, the University of North Carolina at Chapel Hill, Chapel Hill, North CarolinaSearch for more papers by this author First published: 28 April 1989 https://doi.org/10.1002/9781118619179.ch4Citations: 41 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary This chapter examines structural equation models with observed variables. First, they are the most common structural equation models. Second, these models are a special case of the more general structural equation procedures with latent variables that are discussed in the chapter. The major topics of the chapter-model specification, the implied covariance matrix, identification, and estimation—will recur for the other models. The maximum likelihood (ML) and generalized least squares (GLS) ones are asymptotically efficient when the assumption of multinormality holds or when the distribution of the variables have normal kurtosis, whereas the unweighted least squares (ULS) generally is inefficient. The chapter discusses several other topics that arise when utilizing observed variable models. These are standardized and unstandardized coefficients, alternative assumptions for x, interaction terms, and equations with intercepts. Citing Literature Structural Equations with Latent Variables RelatedInformation

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
小浪矢完成签到,获得积分10
2秒前
随风发布了新的文献求助10
2秒前
水水的完成签到 ,获得积分10
3秒前
777完成签到,获得积分20
3秒前
4秒前
5秒前
6秒前
科目三应助decipher采纳,获得10
6秒前
xvan完成签到 ,获得积分10
6秒前
开心枣枣完成签到 ,获得积分10
7秒前
慕青应助小浪矢采纳,获得10
7秒前
万木春完成签到 ,获得积分10
9秒前
orixero应助1783332789采纳,获得10
9秒前
maomao201026完成签到,获得积分10
10秒前
CipherSage应助安河桥采纳,获得10
10秒前
ldh发布了新的文献求助10
10秒前
10秒前
zzd完成签到,获得积分20
12秒前
四喜丸子应助阿聪采纳,获得10
13秒前
乐空思应助阿聪采纳,获得100
13秒前
Kao应助阿聪采纳,获得10
13秒前
13秒前
Kao应助阿聪采纳,获得10
13秒前
方青松应助阿聪采纳,获得10
14秒前
赘婿应助清爽采纳,获得10
14秒前
16秒前
16秒前
16秒前
NexusExplorer应助科研通管家采纳,获得10
16秒前
李健应助科研通管家采纳,获得10
16秒前
1783332789完成签到,获得积分10
16秒前
Akim应助科研通管家采纳,获得10
17秒前
丘比特应助科研通管家采纳,获得30
17秒前
cqk123应助科研通管家采纳,获得10
17秒前
烟花应助科研通管家采纳,获得10
17秒前
情怀应助科研通管家采纳,获得10
17秒前
17秒前
cdercder应助科研通管家采纳,获得10
18秒前
瓶盖应助科研通管家采纳,获得10
18秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Pediatric Dermoscopy Trichoscopy & Onychoscopy 2030
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7576585
求助须知:如何正确求助?哪些是违规求助? 9156198
关于积分的说明 19587954
捐赠科研通 7160479
什么是DOI,文献DOI怎么找? 3265053
关于科研通互助平台的介绍 2430187
邀请新用户注册赠送积分活动 2255662