Model fit during a Confirmatory Factor Analysis (CFA) in AMOS

This is a model fit exercise during a CFA in AMOS. I demonstrate how to build a good looking model, and then I address model fit issues, including modification indices and standardized residual covariances. I also discuss briefly the thresholds for goodness of fit measures.

Category:

Education

Tags:

• Statistics
• AMOS
• CFA
• Factor Analysis
• SEM

[stataguy]

why can't we covarite the error terms of different factors? what if there is methodological issue, for example, similar wording for survey questions? can you suggest a reference for this, please? thanks.

[Gaskination]

@stataguy The detailed answer is yes, you can covary any errors if there is a good reason for systematic correlation of residuals. However, if the correlation is due to a causal relationship (rather than similar wording - thus systematically related), then you should not covary them. In the video I try to keep it simple. Hope this helps. I can't think of a reference off the top of my head.

[ATarhini]

Hello, Do i have to inculde the moderating variables such as Culture constructs (like power distance, uncertainty avoidance...) in the CFA, m measuring the culture using 7 likert scale. cheers

[Gaskination]

@ATarhini

I don't know if there is a right or wrong answer to this. I would include in the CFA all latent variables that I intended on using in my model. This would establish that they are distinct constructs. Moderators, in particular, should not be strongly correlated with the other variables in the model, so I would include them just to make sure they meet this criteria.

[tony287410]

@Gaskination

Thank you for explaining complex things in simple way. my queries are: what is the importance of model fit in CFA, can we interpret that the model established in model fit is statistically approved . What will be the next step to check cause and affect relationships among the latent constructs can you provide link from your videos. Many thanks

[Gaskination]

@tony287410 We do model fit during the CFA in order to establish that the factor structure we have come up with is a satisfactory one. The next thing you would do to establish causality is to start drawing regression lines between the latent constructs. Check out my video "From Measurement Model to Structural Model in AMOS".

[ATarhini]

@Gaskination Many thanks !!

[Gaskination]

@ATarhini If they are reflective (interchangeable) and you have six of them, I would probably just remove one.

[ATarhini]

@Gaskination But would it cause issues when doing the construct validity later on ? as the CR for those two varaibles are < .41 and .45 respectively. knowing that I have 6 variables to measure this construct. deleting two will not be a problem i think