Exploratory Factor Analysis using SPSS ................

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  • Опубліковано 15 гру 2024

КОМЕНТАРІ • 21

  • @MyEasyStatistics
    @MyEasyStatistics  Рік тому +1

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  • @gothandamoorthyc1376
    @gothandamoorthyc1376 4 роки тому +1

    Thank you. Very useful

  • @cunghoctienganh
    @cunghoctienganh 4 роки тому

    I am currently doing this for my PhD thesis.
    My Kaiser-Mayer is above 0.9 which is good
    In my research, there are 18 variables but following your instruction, I have 14 components and most rate above 0.5 belong to component 1. I am confused now. Actually I do not know what to do next. Could you help me?

    • @MyEasyStatistics
      @MyEasyStatistics  4 роки тому +1

      Email me the details to gnsatishkumar@gmail.com

    • @cunghoctienganh
      @cunghoctienganh 4 роки тому

      My Easy Statistics hi Satish, I have sent you the email

  • @akromnasirov5158
    @akromnasirov5158 4 роки тому +2

    To be honest, this is one of the best-explained videos which I've watched and noted some other videos I understand nothing!! But I found what I was looking for on your great explanations! May I leave a question, please? As you have 17 variables, why the components are 5 in your statistics?

    • @MyEasyStatistics
      @MyEasyStatistics  4 роки тому

      17 variables form into 5 components/factors in the analysis

    • @akromnasirov5158
      @akromnasirov5158 4 роки тому

      @@MyEasyStatistics
      Component Initial Eigenvalues
      Total
      1 10.116
      2 4.025
      3 2.075
      4 1.606
      5 1.371
      6 1.242
      7 1.073
      8 1.007
      Here as you can see sir, my components from 2 and 3 greater than 1, in this situation what may I do? Do I have to delete the component 2 and 3 or what please?

    • @MyEasyStatistics
      @MyEasyStatistics  4 роки тому

      The items in your research are forming into 8 components

    • @akromnasirov5158
      @akromnasirov5158 4 роки тому

      @@MyEasyStatistics Thank you so much sir ! Do I not have to delete component 1 and 2 because of higher than 1?

    • @MyEasyStatistics
      @MyEasyStatistics  4 роки тому

      Don't delete

  • @kossonouprunelle7576
    @kossonouprunelle7576 3 роки тому

    Sorry, I have both nominal and ordinal variable in my questionnaire, i took items from previous stuies and translate from english to french. Which one should i choose between EFA and CFA to check reliability and validity of my questionnaire? or should i use both of them? Thanks for your reply.

  • @lovekerni718
    @lovekerni718 3 роки тому

    Sir how many maximum factors can be analysed using kmo?

  • @sunparth
    @sunparth 3 роки тому

    Sir, my Msc students is working of Family Farming Efficiency. It is measured with the help of likert scale on 5 point continuum. Scale consisting total 66 statements, out of which some are positive and some are negative. Total sample 140. KMO and Barlet test indicates sample adequacy and specificity. When I did PCA, considering eigen value more than 1, then total 21 factors are identified. Rotated component explaining 73% variation. Total 21 factors....isn't it more number of component. Is there any solution? Considering PG students time and resource I dont want to assign such bulky work. Please give me your valuable Inputs. Actually I am working as a Subject Matter Specialist in Agricultural University. She is doing PG in Agricultural Extension Discipline. Thanking you

  • @salosarat
    @salosarat 4 роки тому

    what if in any one component none of the questions determine value greater than 0.5 do we need to delete that component?

    • @MyEasyStatistics
      @MyEasyStatistics  4 роки тому +1

      Yes

    • @salosarat
      @salosarat 4 роки тому

      @@MyEasyStatistics Thank you! also the variables that have attained higher eigen values will be further used in CFA or in hypotheses testing? pls help

    • @MyEasyStatistics
      @MyEasyStatistics  4 роки тому

      Yes

    • @salosarat
      @salosarat 4 роки тому

      @@MyEasyStatistics when should we use maximum likelihood method and when should we use principal components

  • @ishitaasinha2498
    @ishitaasinha2498 4 роки тому

    Isn't it wrong to carry factor analysis on Likert scale?