Table Of Contents
  • Multi-sample Analysis LISREL
  • LISREL Data Management
  • Causal Models in LISREL
  • Confirmatory Factor Analysis

Multi-sample Analysis LISREL

A multi-sample analysis in LISREL is used to simultaneously analyze a structural equation model in multiple groups, samples, or sub-samples. This type of analysis allows the researcher if the model fits the data and also the differences among groups while taking into account the parameters of the model. In LISREL, a multi-sample analysis syntax includes several sections. These sections contain the algorithm that will be used to analyze each subsequent group. For example, the analysis instructions of the first sample can be found in the first section. These instructions are known as the normal syntax.

LISREL Data Management

The LISREL software package is a renowned estimator of structural equation models (SEMs). It can be used to perform a myriad of analyses like exploratory data analysis, regression, procedures that require factor analysis, and data manipulation. You also use LISREL to import data that has been prepared using other tools such as SAS, SPSS, MS EXCEL, etc. This software is still popular because of the following reasons:

  • It can be used to test constraints
  • It can perfectly handle multi-group comparisons
  • A researcher can decompose specific effects that had been manually done
  • LISREL greatly reduces the complications associated with analysis by regarding all models to have zero means.

Causal Models in LISREL

Causal models are used in social sciences and statistics to measure both direct and indirect effects. You probably already know that whenever you use ordinary least squares regression, you are assuming that the independent variables are error-free. However, it is near impossible to achieve this. We can measure these regression models by estimating the coefficients that have been implied between latent variables. These variables have several seen indicators. This approach is also not reliable because over-identified models can result in several measures of the relationship between latent variables. LISREL can be used to measure the parameters that have been over-identified.

Confirmatory Factor Analysis

Confirmatory factor analysis is a technique used by researchers to check the factor structure of the variable being observed. This analysis if there is a relationship between the variables that have been observed and the underlying constructs. For example, grades from several tests can be an indicator of intelligence. Single common factor models may be used for confirmatory factor analysis but can be a poor fit for the data. LISREL supports a two-factor model and you can launch it from any windows computer.