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SEM in JASP

Hello!

I am new to this forum and if this is not appropriate, please accept my apologies.


For my master thesis I would like to calculate a SEM like Manis & Choi (2019) (https://ktmanis.com/wp-content/uploads/2018/10/abc.pdf). I would like to use the same model and test for the same parameters. I also have adopted the attached questionnaire. The questionnaire was completed 315 times in total (285 in the study).

If I now try to run PLS SEM in JASP, I get a bad model fit. If I perform only one SEM (like in the study), the model does not converge.

I've tried different things over the past two weeks and I am starting to get desperate. I am new to statistics - so any help would be massivly appreciated!!

The code I used for the Model (hopefully alining with the model showed in Manis & Choi (2019):

AgeM =~ Age

PerceivedEnjoyment =~ PE1 + PE2 + PE3 + PE4

IntentionUse =~ IU1 + IU2 + IU3 + IU4

IntentionPurchase =~ IP1 + IP2 + IP3 + IP4

Curiosity =~ CU1 + CU2 + CU3 + CU4

AttitudeUse =~ AU1 + AU2 + AU3 + AU4 + AU5

Price =~ PP1

PastUseM =~ PastUse

PerceivedUsefulness =~ PU1 + PU2 + PU3 + PU4 + PU5

AttitudePurchase =~ AP1 + AP2 + AP3 + AP4 + AP5

PerceivedEaseUse =~ PEU1 + PEU2 +PEU3 + PEU4 + PEU5


IntentionPurchase ~ PerceivedUsefulness + PerceivedEnjoyment + AttitudePurchase

IntentionUse ~ AttitudeUse + PastUseM

AttitudePurchase ~ PerceivedUsefulness + PerceivedEnjoyment + PerceivedEaseUse

AttitudeUse ~ PerceivedUsefulness + PerceivedEnjoyment + PerceivedEaseUse

PerceivedEnjoyment ~ Price + PerceivedEaseUse

PerceivedUsefulness ~ AgeM + PastUseM + Price + PerceivedEnjoyment + PerceivedEaseUse

PerceivedEaseUse ~ AgeM + Curiosity + PastUseM + Price


Comments

  • AgeM =~ Age
    Price =~ PP1
    PastUseM =~ PastUse
    

    at a minimum I'm guessing you have a problem with these 3 factor definitions, as these are phantom constructs, and I can't imagine this is the right syntax for them (specifically, you probably need to add some constraint on them, like AgeM =~ 1*Age for example). You can google phantom constructs with lavaan in R (JASP uses the lavaan library)

    Also make sure your variables in your dataset (leftmost panel in JASP) are scale variables, i.e. with an orange ruler icon (not ordinal)

  • Hey patc3!

    Thank you so much for your answer! Should I change the varibles despite this is a ordinal data?

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