Hello, professor. Thank you for your video.😃 My question: How can I perform a strict invariance analysis to make the variances equal? I have tried typing "group.equal=c("loadings","intercepts","variances"))", but the console shows "Error in lav_options_set(opt): lavaan ERROR: unknown value for `group.equal' argument: ‘variances’". Thank you in advance~😆
Hi, first of all thanks this clear and nice demonstration! I've ran the same models and seemed to work pretty good for me, but now I'm stuck: I need to save the factor scores from the last model (constrained) and attach them to my dataframe. How could I do that? Thanks
When running my configural model, I get the following error: (Warning message: In lav_object_post_check(object) : lavaan WARNING: some estimated ov variances are negative) how can this be resolved?
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Hello, professor. Thank you for your video.😃
My question: How can I perform a strict invariance analysis to make the variances equal? I have tried typing "group.equal=c("loadings","intercepts","variances"))", but the console shows "Error in lav_options_set(opt):
lavaan ERROR: unknown value for `group.equal' argument: ‘variances’". Thank you in advance~😆
Hi, first of all thanks this clear and nice demonstration!
I've ran the same models and seemed to work pretty good for me, but now I'm stuck: I need to save the factor scores from the last model (constrained) and attach them to my dataframe. How could I do that? Thanks
When running my configural model, I get the following error: (Warning message:
In lav_object_post_check(object) :
lavaan WARNING: some estimated ov variances are negative) how can this be resolved?