LISREL沒有聚類分析功能 (At this time LISREL does not have a Cluster Analysis function.)
您可以連結以下網址,來預覽所有YouTube的教學影片
http://www.youtube.com/user/SoftHomeLisrel
| Lisrel 功能展示 | |
結構方程式原理:
結構方程式-Structural Equation Modeling (SEM）用以同時處理一系列或多組自變項和應變項之間的關係,其可透過LISREL軟體加以分析。描述潛在變數間之因果關係,LISREL模式特別適用於一模型：包括潛在變數、獨立變數及應變數之測量誤差、雙向因果關係,同時發生及相互依賴性。
功能與特色:
LISREL最大的特點在於探討多變項或單變項之間的因果關係.
1. 結構方程模型-LISREL
2. 資料操作和基本統計分析-PRELIS
3. 順序變數的因素分析-Ordinal Variables
4 建構潛在曲線模型-Structured Latent Curve Models
5. 一般線性模型-SURVEYGLIM
6. 層級線性和非線性模型-MULTILEV
7. 多層級資料的一般線性模型-MAPGLIM
8. 類別變數的處理-CATFIRM
9. 連續變數的處理-CONFIRM
10. 觀察變數殘差-Observational Residuals
11. 寫入參數、標準差估計值和PSF測量
12. 更完善的圖型使用者介面- (GUI)
LISREL (LInear Structural RELations)是由K.G. Joreskog & D. Sorbom所發展的結構方程模型(Structural Equation Modeling)軟體. 是目前最常用的SEM軟體.只要是SEM的分析方法幾乎都包含在內. 目前幾乎可在各平臺執行包含Windows, Mac OS 9 X, Solaris, AIX, RISC ,OpenVMS , Linux等. LISREL的內容包含多層次分析(multilevel analysis),二階最小平方估測(two-stage least-squares estimation),主成份分析(principal component analysis)等等. 實際應用範例及其相關連結:
9.以負向情感訴求公益廣告效果傳遞模式之效度驗證：中美日三國比較
10.供應作業電子化、交易關係模式與供應績效關係之研究－台灣資訊電子製造業之實證
中文書籍推薦:
在過去的45年中，LISREL模型，方法和軟件已成為結構方程模型（SEM）的同義詞。SEM使社會科學，管理科學，行為科學，生物科學，教育科學和其他領域的研究人員可以憑經驗評估其理論。這些理論通常被公式化為觀察和潛在（不可觀察）變量的理論模型。如果收集了理論模型中觀察變量的數據，則可以使用LISREL程序將模型擬合到數據中。
但是，今天，LISREL不再局限於SEM。LISREL 10包括64位統計應用程序LISREL，PRELIS，MULTILEV，SURVEYGLIM和MAPGLIM。
LISREL是用於標準和多層結構方程建模的64位應用程序。這些方法可用於關於分類變量和連續變量的完整和不完整的複雜調查數據，以及關於分類變量和連續變量的完整和不完整的簡單隨機樣本數據。
PRELIS是64位應用程序，用於數據處理，數據轉換，數據生成，計算矩矩陣，計算樣本矩的估計漸近協方差矩陣，匹配匹配插補，多元插補，多元線性回歸，對數回歸，單變量和多元刪失回歸， ML和MINRES探索性因素分析。
MULTILEV是一個64位應用程序，可將多級線性和非線性模型與簡單隨機和復雜調查設計中的多級數據擬合。它允許具有連續和分類響應變量的模型。
SURVEYGLIM是一個64位應用程序，適用於廣義LInear模型（GLIM）與簡單隨機和復雜調查設計中的數據。提供了多項式，伯努利，二項式，負二項式，泊松，正態，伽瑪和反高斯採樣分佈的模型。
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During the last forty five years, the LISREL model, methods and software have become synonymous with structural equation modeling (SEM). SEM allows researchers in the social sciences, management sciences, behavioral sciences, biological sciences, educational sciences and other fields to empirically assess their theories. These theories are usually formulated as theoretical models for observed and latent (unobservable) variables. If data are collected for the observed variables of the theoretical model, the LISREL program can be used to fit the model to the data. Today, however, LISREL is no longer limited to SEM. LISREL 10 includes the 64-bit statistical applications LISREL, PRELIS, MULTILEV, SURVEYGLIM and MAPGLIM. |
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LISREL is a 64-bit application for standard and multilevel structural equation modeling. These methods are available for the complete and incomplete complex survey data on categorical and continuous variables as well as complete and incomplete simple random sample data on categorical and continuous variables.
PRELIS is a 64-bit application for data manipulation, data transformation, data generation, computing moment matrices, computing estimated asymptotic covariance matrices of sample moments, imputation by matching, multiple imputation, multiple linear regression, logistic regression, univariate and multivariate censored regression, and ML and MINRES exploratory factor analysis.
MULTILEV is a 64-bit application that fits multilevel linear and nonlinear models to multilevel data from simple random and complex survey designs. It allows for models with continuous and categorical response variables.
SURVEYGLIM is a 64-bit application that fits Generalized LInear Models (GLIMs) to data from simple random and complex survey designs. Models for the Multinomial, Bernoulli, Binomial, Negative Binomial, Poisson, Normal, Gamma, and Inverse Gaussian sampling distributions are available.
MAPGLIM is a 64-bit application that implements the Maximum A Priori (MAP) method to fit generalized linear models to multilevel data.
