A guide to SEM analysis procedures
SEM is used to build structural links between measured variables and latent constructs. This article provides a detailed description of the SEM analysis procedures.
analysing with amos, SEM module
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Introduction to quantitative data analysis methods
This article is about commonly used methods in small program evaluation with examples. Quantitative data helps with quantifiable results.
analyse with SPSS, sem introduction, spss introductionDifferent types of structural equation modeling analysis
There are five major types of structural equation modeling analysis. Each of them helps to build a relationship between variables.
sem introduction, SEM moduleCriteria for reliability and validity in SEM analysis
The principles of validity and reliability in SEM are used to assess the quality of research. They reflect the accuracy with which a method, approach, or test measures a problem.
analysing with amos, research validity, SEM moduleWhat is Structural Equation Modeling (SEM) analysis?
Structural Equation Modeling (SEM) analysis is a statistical method used in social science studies for testing the linkage between multiple variables at any point in time. SEM analysis is an extension of the simple linear model.
research data analysis, sem introduction, SEM moduleIdentification of statistical tools to aid in biomarker analysis
Biomarker discovery starts with a small number of samples in the form of preclinical exploratory studies to identify promising biomarkers form a pool of diseased and non-diseased groups.
Importance of Molecular Biomarkers in Non-communicable diseasesJoint frequencies analysis using Hamlet II
Joint frequencies analysis helps to search inter-connections between a number of keywords or character strings occurring in the text. It produces matrices of joint frequencies of the items of a specified vocabulary list with respect to a suitably chosen unit of context.
hamlet, text data analysisData visualisation using cluster analysis
Cluster analysis serves as an extension to qualitative data representation through data visualisation. It is an exploratory technique for visualising patterns in a study by grouping sources or nodes.
nvivo data representation, nvivo module