JASP 0.13.1 Tutorial: Exploratory Factor Analysis (EFA) (Episode 20)

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  • เผยแพร่เมื่อ 2 ธ.ค. 2024

ความคิดเห็น • 37

  • @Tanjura
    @Tanjura ปีที่แล้ว +4

    Thank you for all your JASP tutorials! I'm using JASP for my bachelor thesis in legal psychology as an affordable alternative to SPSS and wouldn't have been able to learn it that quickly without your videos (and time is of the essence). So your efforts are very much appreciated.

  • @54gulnara
    @54gulnara ปีที่แล้ว +1

    Good, it works for me. If the original dataset is available to reproduce outputs, please let us know.

  • @ricekul
    @ricekul 11 หลายเดือนก่อน

    Thank you for the tutorial. Is there a tutorial that explains Regularized Exploratory Factor Analysis (REFA)? Thank You.

    • @AlexanderSwan
      @AlexanderSwan  11 หลายเดือนก่อน

      I’m not familiar with that technique, so I am unsure if it is possible in JASP

  • @blessing_motene5766
    @blessing_motene5766 ปีที่แล้ว

    hi, i need major help with how to examine the dimensionality of the data (bear in mind that although the intention was to develop two scales, it is possible that the 30 items measure more than two major traits or dimensions) how do i do this

    • @AlexanderSwan
      @AlexanderSwan  ปีที่แล้ว

      This isn’t something I can help with without looking at your data and output, sorry

  • @seed6006
    @seed6006 2 ปีที่แล้ว

    Great Teaching,!.. ❤️May I ask...Does Uniqueness in Factors matter???.. I've seen your uniqueness values abOve 0.4... Do I have to remove all the questions that Have below 0.4 value in the Uniqueness as I do The Exploratory Factor Analysis???.. Thank you💙

    • @AlexanderSwan
      @AlexanderSwan  2 ปีที่แล้ว

      This is a convention among statisticians -- .40 is seen as a good level for an item to be a good contribution to the factor. Items below that value don't contribute much to the factor, so they can likely be removed. If you don't remove them, nothing much changes, but you might get questions as to why they're still there

    • @seed6006
      @seed6006 2 ปีที่แล้ว

      @@AlexanderSwan Thanks❤️

  • @daypetal
    @daypetal ปีที่แล้ว

    good day, alexander, and thank you for the tutorial! if i'm allowed to ask a question, i have one question. if i test my data from multidimensional inventory with EFA, should i test the data's reliability per its dimension or with the factor from the EFA result? thank you in advances!

    • @AlexanderSwan
      @AlexanderSwan  ปีที่แล้ว

      Always test reliability within dimensions before and after running your factor analysis.

    • @daypetal
      @daypetal ปีที่แล้ว

      @@AlexanderSwan thank you for your answer, it helps me a lot!

  • @anyidxt8168
    @anyidxt8168 3 ปีที่แล้ว +1

    Thank you for your videos Alexander! Could you please make a tutorial about how to perform Confirmatory Factor Analysis in JASP using a grouping variable, for example Gender as a grouping variable. Thank you!

    • @AlexanderSwan
      @AlexanderSwan  3 ปีที่แล้ว +1

      Sure. I'm not sure how well that will work, but I can give it a shot. I am not super well-versed in all the measurements/fit indices for CFA, but I'll see what JASP has to offer on this front.

  • @viktoria7665
    @viktoria7665 2 ปีที่แล้ว

    Hi, and thank you for the informative video. I was wondering what the scores under "cumulative" under "factor characteristics" tells us? If I understood it correctly the proportion var. tells us how much of the modell is explained by the factors. But I am not sure about the cumulative. Anyway, thank you for the video

    • @AlexanderSwan
      @AlexanderSwan  2 ปีที่แล้ว

      Cumulative usually sums to 100%

  • @ivynn7669
    @ivynn7669 3 ปีที่แล้ว

    what to do if the variables are originally nominal?? and it cant be changed into scale :(

    • @AlexanderSwan
      @AlexanderSwan  3 ปีที่แล้ว +1

      While you *can* perform an FA with nominal data, it won't look good. This is because an FA is a matrix of Pearson correlations, which you cannot use nominal data with, anyway.
      Thus, I don't recommend. If you are looking for nominal correlations, you want polychoric, but JASP can't do that.

    • @ivynn7669
      @ivynn7669 3 ปีที่แล้ว

      @@AlexanderSwan oh gosh I thought I wouldnt get a reply, thank you so much for this and you are an actual blessing

  • @macymaddison8303
    @macymaddison8303 7 หลายเดือนก่อน

    How do we interpret results tho

    • @AlexanderSwan
      @AlexanderSwan  7 หลายเดือนก่อน

      That’d be in another video made by someone else. I do minimal interpretation, rather here I just show users how to use the module.

  • @MissSqueezi
    @MissSqueezi 2 ปีที่แล้ว

    Hey there! Thank you so much - this was very helpful!
    Could you explain to me how to calculate a item-total-correlation in JASP?

    • @AlexanderSwan
      @AlexanderSwan  2 ปีที่แล้ว

      I'm not sure where that function is in JASP. I'd have to look.

  • @Broekh01
    @Broekh01 ปีที่แล้ว

    Helpful. Thank you.

  • @icarocosta4302
    @icarocosta4302 3 ปีที่แล้ว

    thanks! where is the "explained variance"?

    • @AlexanderSwan
      @AlexanderSwan  3 ปีที่แล้ว +1

      "Explained variance" is not an output but rather how you interpret correlations and factor loadings. So it's just something I say when talking about the results!

    • @icarocosta4302
      @icarocosta4302 3 ปีที่แล้ว

      @@AlexanderSwan só, is not possible to get this information?

    • @AlexanderSwan
      @AlexanderSwan  3 ปีที่แล้ว

      @@icarocosta4302 I'm not following your question.

    • @icarocosta4302
      @icarocosta4302 3 ปีที่แล้ว

      @@AlexanderSwan that % of explained varience. Is not possible to get it from jasp?

    • @AlexanderSwan
      @AlexanderSwan  3 ปีที่แล้ว

      @@icarocosta4302 oh I see. It is in the output as the load coefficients. Then you just use that to discuss variance

  • @gna3706
    @gna3706 3 ปีที่แล้ว

    absolute legend

  • @Bioexploration360
    @Bioexploration360 4 ปีที่แล้ว

    Great sir 👍 am waiting for this
    Thanks

  • @rusdiismail9566
    @rusdiismail9566 3 ปีที่แล้ว

    tq sir.. very usefull