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hyunsooseol / snowRMM

Latent Class Analysis(LCA), LCA for ordinal indicators, Latent class growth modeling, Laten Profile Analysis, Rasch model, Linear Logistic Test Model, Rasch mixture model, linear and equipercentile equating can be performed within module.
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New features to LCA #12

Closed andremonezi closed 7 months ago

andremonezi commented 2 years ago

Hello Dr. Seol, Thank you for your fantastic work on this Jamovi module. Besides BIC and AIC, it would be great if you would include new estimators to evaluate the fit of the model (SABIC = sample-size adjusted BIC; AWE = approximate weight of evidence criterion; CAIC = consistent Akaike information criterion; BF = Bayes factor; ALCPP = average latent class posterior probability; VLMR-LRT = Vuong-Lo-Mendell- Rubin adjusted likelihood ratio test. See the attached article for some very interesting indicators that can further improve the quality of data interpretation. I believe these same indicators 'can also be inserted into Latent Profile Analyses. Best regards LCA guide.pdf

hyunsooseol commented 2 years ago

Hi andremonezi

Thanks for providing useful paper in LCA. I wonder if there is a package that provides those kinds of fit index in R programs. I'll look for it sometime.

Cheers Seol

andremonezi commented 1 year ago

Hi Dr. Seol, Any news about these features? Best regards

hyunsooseol commented 1 year ago

Hi andremonezi

I implemented those statistics to snowRMM:: Latent Profile Analysis.

Cheers Seol

hyunsooseol commented 1 year ago

Hi andremonezi

I added ABIC and CAIC index and covariates option in LCA inside snowRMM.

Best Regards Seol

VeraLZ commented 1 year ago

Dear Dr. Seol, Thank you so much to provide this module. I would like to ask you if it would be possible to add a elbow plot to show the gains associated with additional profiles in LPA to help us to identify when the improvement in fit reaches a plateau and additional profiles become negligible thereafter. Thank you very much

hyunsooseol commented 1 year ago

Hi

I am trying to add Elbow plot in LPA.

It will be available this week. I will let you know.

Best Seol

Hyunsoo Seol, Ph.D., Professor

Dept.of Education, Chung-Ang Univ.

c.p) 010-3294-5717, o) 820-5370

H) http://jamovi.krhttp://jamovi.kr/

[cid:958207ac-152e-4023-bf19-8d39f31e955e]

보낸 사람: VeraLZ @.> 보낸 날짜: 2022년 11월 28일 월요일 오후 8:30 받는 사람: hyunsooseol/snowRMM @.> 참조: 설현수 @.>; Comment @.> 제목: Re: [hyunsooseol/snowRMM] New features to LCA (Issue #12)

Dear Dr. Seol, Thank you so much to provide this module. I would like to ask you if it would be possible to add a elbow plot to show the gains associated with additional profiles in LPA to help us to identify when the improvement in fit reaches a plateau and additional profiles become negligible thereafter. Thank you very much

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hyunsooseol commented 1 year ago

Hi

It is available in LCA and LPA inside snowRMM module. Update from jamovi library now. image

Best Regards Seol

VeraLZ commented 1 year ago

Dear Professor Seol,

Thank you so much to add a elbow plot and for your fantastic work on Jamovi.

Best regards