CFA, EFA, Co-Variance based SEM through SPSS AMOS and PLS - SEM

[Ajit Maurya]

Dear Neeraj Sir and other group members,

I wanted to know the difference between usage of 

1) Confirmatory Factor Analysis

2) Exploratory Factor Analysis
3) Co-Variance Based SEEM through SPSS AMOS
4) PLS - SEM through SMART PLS 4.0

How to use these techniques ?

Regards,

Ajit Maurya

Research Scholar - Somaiya Vidyavihar University
Mobile No: 7208625413

[Shriya Sharma]

1. EFA: exploratory factor analysis is a technique for identifying groups or clusters of variables, which has three main uses: to understand the structure of the set of variables; to construct a questionnaire to measure an underlying variable; and to reduce a dataset to a more manageable size.

When to use EFA: when there is no existing theory or literature available in the existing literature and we are the first to establish scales in such an area. 

How to use EFA: In SPSS, you can perform EFA. 

2. CFA: is used when researchers have a well-formed hypothesis or theory about the relationship. It is conducted to validate the constructs. CFA rigorously tests the model against the observed data to determine its fit and validity.

When to use CFA: when the established scale items are taken from the existing studies for the survey, we apply CFA to test the reliability, validity, and model fitness. In such a case, EFA is not applied. 

How to use CFA: We can calculate reliability, validity, and model fitness in AMOS, SPSS, and SmartPls. The choice of software depends on certain conditions.

For deeper knowledge regarding EFA and CFA, kindly refer to 

1.  DISCOVERING STATISTICS USING Spss by Andy Field 

2. Multivariate Data Analysis Joseph F. Hair Jr. and William C. Black Barry J. Babin Rolph E. Anderson

3. Covariance SEM: when the research objective is theory testing and confirmation, we use CB-SEM, and the software is AMOS. Kindly refer to  PLS-SEM or CB-SEM: updated guidelines on which method to use by Hair et al. (2017).

4. PLS-SEM: If the research objective is prediction and theory development, the appropriate method is PLS-SEM. When data is nonnormal, the sample size is less than one hundred, the structural model is complex and includes many constructs, the path model includes one or more formative constructs, research requires latent variable score for follow-up analysis, etc. For more knowledge, kindly refer to the research article: WHEN TO USE AND HOW TO REPORT THE RESULTS OF PLS-SEM by Hair et al. 2019. 

Regards

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[Ajit Maurya]

Dear Ma'am,

Thank You very much.

Regards,

Ajit Maurya

[Neeraj Kaushik]

Also watch https://www.youtube.com/watch?v=O6h9Iajvu_U&list=PLzUJUtTJcj8Tub9LHkIBBScx0N6DyBMWL&index=12

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