Robustness Checks

In this video titled: Unobserved Heterogeneity using SmartPLS4, We will discuss how to use SmartPLS4 to assess the unobserved heterogeneity. By the end of this video, you'll have a clear understanding of how to assess unobserved heterogeneity in your research using SmartPLS4 and make informed decisions to enhance the robustness of your findings.
Contents
00:13 - Introduction to Unobserved Heterogeneity
00:53 - The Importance of Assessing Unobserved Heterogeneity
01:36 - Selection Criteria for Assessing Heterogeneity
02:16 - Determining the Sample Size for Segments
04:22 - Analyzing Results for Different Segments
08:09 - Interpreting Fit Indices for Segmentation
10:29 - Handling Ambiguity in Segmentation Results
11:15 - Conclusion and Implications
Do you have any questions, tips, or ideas? Let me know in the comments section below!
About:
Research With Fawad is a Research initiative to help young and early career research learn the research tools and techniques. It is an initiative to share research knowledge and help researchers learn to research the easy way.
Learn more about Research With Fawad at www.researchwithfawad.com.
#SmartPLS4 #UnobservedHeterogeneity #StructuralEquationModeling

[@francisarthur2983]

Thank you Prof. Fawad for the scholarly presentation.

[@researchwithfawad]

You are welcome

[@Alhamzah_F_Abbas]

Well done prof. Could you please share the 2 papers title you just presented. Thank you

[@researchwithfawad]

thanks for watching. Please refer to
Sarstedt, M., Ringle, C. M., Cheah, J. H., Ting, H., Moisescu, O. I., & Radomir, L. (2020). Structural model robustness checks in PLS-SEM. Tourism Economics, 26(4), 531-554.

[@abadirroba6747]

Professor how are you doing. as usual i am enjoying your videos. i do have a question for you. my FIMIX-PLS analysis identified two segments in the data but 94.3% of the data is in segment 1, segment 2 only has 5.7% of the data. when i try to create two group SmartPLS only generate one group even though i add group two the analysis couldn't be computed because it says the data in segment two is not sufficient for analysis. so should i conclude that there is no unobserved heterogeneity issue in my data? or is there any other mechanisms to check heterogeneity issues

[@researchwithfawad]

Thanks for watching. Use One Segment for Analysis

[@ghazniabbasi311]

Thanks for the video. I have observed that in one of my datasets the number are heading me to 5 segments. AIC AIC3, AIC4, BIC and CAIC inform me that I have 5 segments, what do we do? how do we analyzes in this case? Thanks

[@researchwithfawad]

Thanks for watching. Did you check MDL5?
You may please read
Sarstedt, M., Ringle, C. M., Cheah, J. H., Ting, H., Moisescu, O. I., & Radomir, L. (2020). Structural model robustness checks in PLS-SEM. Tourism Economics, 26(4), 531-554.

[@ghazniabbasi311]

Thank you for replying. Yes i have and i am in some kind of dilema. Anyways, can i have your email please? I would like to reach out to you for further discussions. Thanks again for your kindness

[@hassaanahmad4770]

Ok I understand this, but I have a question, I have collected data from two different samples now what should I do because as I run the test the results are horrible???

[@researchwithfawad]

You may divide the data into groups and see which groups perform badly and remove them. You may collect more data.