Hello everyone,
hope you can help me with this as I am stuck in my data analysis.
I know I can obtain unstandardized latent variable scores from the IPMA. I also read online lots of articles discussing Hypothesis testing through the latent factor scores. My questions are:
I need to carry out a t-test to test differences between two latent variables of two different groups. Can I use the Latent variable scores as they are provided by the IPMA for each observation or do I need to compute any sort of adjustment? Meaning, can I copy and paste those LVS in SPSS for all the observation and then carry out my T-test? Although I read several posts and articles on the matter I could not find any clear indication on whether I could simply copy and paste those scores or whether I need to adjust them for the number of items etc.
Also, providing that I am comparing two different groups form two different population, would be good to check first for measurement invariance?
Hope you can help me with the above cause I am really stuck and do not know how to proceed further.
Thank you!
Can I use the unstandardised latent variable scores as they are provided in the IPMA for hypothesis testing (t-test)?
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Re: Can I use the unstandardised latent variable scores as they are provided in the IPMA for hypothesis testing (t-test)
First, yes you should check for measurement invariance.
Second, when you test for measurement invariance, in step 3 you get a permutation estimate of the mean differences which is similar to the t-test that you want to calculate. Hence, you might just use this (assuming that you have measurement invariance in step 2).
Third, generally, if you have measurement invariance in step 2 you could also copy the unstandardized LV scores from the IPMA on each group and use a t-test. However, you are then leaving the realm of nonparametric testing. One of the main reasons for why people use PLS. This brings you back to second.
Second, when you test for measurement invariance, in step 3 you get a permutation estimate of the mean differences which is similar to the t-test that you want to calculate. Hence, you might just use this (assuming that you have measurement invariance in step 2).
Third, generally, if you have measurement invariance in step 2 you could also copy the unstandardized LV scores from the IPMA on each group and use a t-test. However, you are then leaving the realm of nonparametric testing. One of the main reasons for why people use PLS. This brings you back to second.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de