Moderation

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Bellsie
Posts: 52
Joined: Wed Apr 24, 2019 9:20 am

Moderation

Post by Bellsie »

Hello!
I hope you are well.
I have a question about moderation.
It worked perfectly with Catastrophe as predictor and distress as moderator (with a selection of dependent variables)
I am trying to do the samewith Accidents as predictor but the outcome is NaN. I can't find the text in the data...
Please could you help me?
Thank you
Lottie
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Secouristes Avril 2020.omv
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Bellsie
Posts: 52
Joined: Wed Apr 24, 2019 9:20 am

Re: Moderation

Post by Bellsie »

I think the problem is with distress - I might have clicked on something wrong...
Bellsie
Posts: 52
Joined: Wed Apr 24, 2019 9:20 am

Re: Moderation

Post by Bellsie »

If you could have a glance at the dataset I would be so grateful!
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jonathon
Posts: 2613
Joined: Fri Jan 27, 2017 10:04 am

Re: Moderation

Post by jonathon »

hi bellsie,

moderation isn't something i know much about, but hopefully someone else will chime in.

cheers

jonathon
Bellsie
Posts: 52
Joined: Wed Apr 24, 2019 9:20 am

Re: Moderation

Post by Bellsie »

Thank you. The problem s that my "distrss" variable is coming u as NaN no mattre what i do about it...
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jonathon
Posts: 2613
Joined: Fri Jan 27, 2017 10:04 am

Re: Moderation

Post by jonathon »

actually, let me attend ravi to this.

jonathon
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jonathon
Posts: 2613
Joined: Fri Jan 27, 2017 10:04 am

Re: Moderation

Post by jonathon »

hi bellsie,

we're not sure what the issue is here. the medmod analyses rely on a package called 'lavaan', and NaN is just the results that lavaan provides here. i think the issue stems from the extreme values in the DISTRESS variable.

if i apply the filter DISTRESS < 50 this filters out 3 cases, and i receive a result. looking at the DISTRESS variable, it seems highly skewed, and in lots of other analyses a lot transform can be appropriate, but i don't know enough about medmod to say if that would be appropriate here.

cheers

jonathon
Bellsie
Posts: 52
Joined: Wed Apr 24, 2019 9:20 am

Re: Moderation

Post by Bellsie »

I cannot thank you enough! You are all stars!
Lottie
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