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Confirmatory Factor Analysis; Patrick Sturgis (part 3 of 6)

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  • čas přidán 15. 08. 2024
  • Professor Patrick Sturgis, NCRM director, in the third (of three) part of the Structural Equiation Modeling NCRM online course.
    This video is part of the online learning resources from the National Centre for Research Methods (NCRM). To access the supporting materials (presentation slides, datasets, recommended reading, links to related publications and resources) visit www.ncrm.ac.uk/...

Komentáře • 67

  • @dongxu2257
    @dongxu2257 Před 2 lety +10

    As a professor myself, I truly appreciate the way Prof. Sturgis present the course - focusing on intuition rather than mathematics, which in my view is of great importance for non-statistical students.

  • @annabellegadabu7566
    @annabellegadabu7566 Před 5 lety +37

    i like the way you explain things slowly and at ease. for someone unfamiliar with statistical analysis at all it's been helpful in understanding SEM. Great job Professor

  • @mbonezakabanda7971
    @mbonezakabanda7971 Před 3 lety +6

    I enjoy the way the Professor explains SEM so that even beginners can understand. Great job, Professor.

  • @MCshaneization
    @MCshaneization Před 4 lety +12

    As a stats instructor myself I am very impressed by the clarity and concision of your presentation. Great job!

  • @tenkolew
    @tenkolew Před 3 lety +4

    The best learning resource I’ve found so far. On point. Clear. Your style calms any anxiety

  • @afpierson
    @afpierson Před 7 lety +16

    This guy is a great speaker and very articulate. Thank you, Professor Sturgis. You took a very complicated topic and made it simple by breaking it down in three separate videos.

    • @jonathanstudentkit
      @jonathanstudentkit Před 6 lety

      he's a very bad speaker loads of ehs, for instance and it's way too slow to stay interested

  • @baburajesh1000
    @baburajesh1000 Před 3 lety +1

    Respected professor,
    Thank you so much for providing more insights on SEM and many of the researchers will get benefited from your teachings.

  • @joseannknight8820
    @joseannknight8820 Před 5 lety +2

    The explanations here are simple yet insightful. A great job Professor!

  • @kevinkelly1960
    @kevinkelly1960 Před 7 lety +5

    Fantastic 3 lectures. Brilliant. Thank you for sharing, Kevin

  • @wjingzhou1967
    @wjingzhou1967 Před 4 lety

    Thank you so much for your concise and clear explaination of SEM in such a slow and elegant way! Gorgeous!

  • @Deborah28277
    @Deborah28277 Před 2 lety

    I’ve watched your videos over and over, each time my SEM understanding increases .. this time around the AHA moment occurred within the Mean Structure discussion , specifically reflexive vs formative indicators when measuring constructs like social capital and imposter syndrome.

  • @bugendijoseph1313
    @bugendijoseph1313 Před 3 lety

    I really enjoy alot listening to professor Patrick sessions on SEM

  • @kiwanukajoseph6668
    @kiwanukajoseph6668 Před 4 lety

    IAM really impressed by the clarity and concision of your presentation. Great job prof !

  • @mafaldacampos799
    @mafaldacampos799 Před 3 lety +1

    Been watching these videos to help me with my master's thesis and it has been a great help. Thank you!

  • @dr.vincentkibambila3003

    Nice work Professor, I like your style of teaching. May God Lord Protect you

  • @students4life821
    @students4life821 Před 3 lety +2

    I need to like this video twice. What a great explanation!

  • @Moe4572
    @Moe4572 Před rokem +1

    Seriously saving me right now :) Can't thank you enough!

  • @KarthikSrinivasanTucson
    @KarthikSrinivasanTucson Před 7 lety +2

    Enjoyed all three talks. Very well made. Thank you

  • @oindrilamukherjee6030
    @oindrilamukherjee6030 Před 2 lety

    Thank you so much Professor, it has been so insightful and helpful learning from you!

  • @areejalmehdar8467
    @areejalmehdar8467 Před 7 lety +3

    amazing lectures! Thank you very much indeed

  • @Flower-62
    @Flower-62 Před 2 lety

    Thanks prof. I suggest to give numerical example and clarify each step.
    Only theory would not be understandable for everyone. Thus if could prepare a numerical example to explain the steps friendly.

  • @wissamkheir
    @wissamkheir Před 6 lety +1

    Thank you so much for this ! Very clear and concise !

  • @syafiqsidqisaidi6337
    @syafiqsidqisaidi6337 Před 3 lety

    thanks Prof on the lecture ! really helpful may God Bless you

  • @sintakristanti6108
    @sintakristanti6108 Před 4 lety

    Thank you so much, very very helpful!!! Please keep making video ...

  • @yingc1233
    @yingc1233 Před 3 lety

    Great series, thank you!

  • @Josefk40
    @Josefk40 Před 4 lety

    This is an awesome lecture. Thank you

  • @texla-kh9qx
    @texla-kh9qx Před 7 měsíci

    Could someone explain what is the definition of degrees of freedom here? Naively, I thought degrees of freedom are free model parameters, but this is in contradictory to the use of the term in the lecture.
    If we apply constraints, the number of free parameters decreases and hence the model becomes less flexible (less capable). How do I understand the fact that the less flexibility implies the larger number of degrees of freedom?

  • @niklaskonig4278
    @niklaskonig4278 Před 7 lety +1

    Great lecture. Thank you! Just noticed, on the first slide "Two Factor, Six Item EFA" there is an one-headed-arrow missing between eta2 and x3. But anyway, great lecture!

  • @l.3890
    @l.3890 Před 6 lety

    Thank you! finally I could understand SEM!

  • @simplyram2676
    @simplyram2676 Před 2 lety

    Hi Dr., how if discriminant validity is NOT met after CFA? But model fit and convergent validity is met. What should we do? Can I do EFA?

  • @priyankagupta2813
    @priyankagupta2813 Před 4 lety

    sir add a line from n2 to x3 @ 18:32.......Your explanation is really v good, easy to understand

  • @kswill4514
    @kswill4514 Před 5 lety

    Better than I've learnt from school

  • @mikojavier2435
    @mikojavier2435 Před 3 lety

    thank you,very clear explanation

  • @AngeloYeo
    @AngeloYeo Před 7 lety +3

    Thank you for such a nice lecture :)

  • @DrMichael_Psychology
    @DrMichael_Psychology Před 7 lety

    That's great, very appreciative.
    Small note: at minute 18 there are only 5 single-headed arrows going from the latent variables to the indicators, not 6.

    • @MohsinUlAminKhan
      @MohsinUlAminKhan Před 7 lety

      That's only for n2, not n1. I guess that is just an unintentional mistake.

  • @MayadaMAref
    @MayadaMAref Před 7 lety

    thank you for these very informative lectures

  • @Goliad2016
    @Goliad2016 Před 3 měsíci

    dear professor if you can please show how to calculate sample size in structural equation model !!!

  • @artimalik1126
    @artimalik1126 Před 2 lety

    Sir, my topic is to measure impact of work-life balance on job satisfaction. I measured these two through different constructs.Items were taken from existing questionnaires of different authors. I combined few constructs and I added and deleted some items form constructs. What should I use CFA or EFA and why. Sir, please guide

  • @laxmanpokhrel2091
    @laxmanpokhrel2091 Před 7 lety

    Remarkably crafted presentation and contents ...Great learning experience...Thank you. ..

  • @MBC999able
    @MBC999able Před 5 lety

    Brilliant lecture

  • @pauljoseph9276
    @pauljoseph9276 Před 4 lety

    Great lecture Prof. you make it very simple to understand. How can i analyse path analysis with categorical data?

  • @wansitihajar5558
    @wansitihajar5558 Před 3 lety

    Thank you Prof, it is informative and came in hand for my research. I have a question regarding the high order factors structure. Why is that the errrors are no longer respective to their observed indicators? such that error 3 points to indicator 1 etc?

  • @michaelpaulse1
    @michaelpaulse1 Před 4 lety

    Thank you for great lectures!
    How do I calculate apriori sample size for CFA - I have seven 1st order and one 2nd order latent variables. Observable items 120 questions predominantly Likert type. Could you please assist?

  • @kritiarora7585
    @kritiarora7585 Před 2 lety

    Hi! Thank you for this great explanation of the CFA. I wanted to ask what is the difference between item parcelling and the higher order factor model? Is item parceling a special case of higher order factor model?

  • @isaackwao608
    @isaackwao608 Před 2 lety

    please prof what is NNI in one factor CFA ?

  • @The-TAPT-Talks
    @The-TAPT-Talks Před 4 lety

    Hi professor
    Can we use 5 levels scale as bellows:
    -2 -1 0 1 2
    for EFA, CFA, SEM analysis?

  • @pulkit21aug
    @pulkit21aug Před 5 lety

    Prof Patrick Sturgis - could you please confirm apart from psychology can SEM be used in other domain e.g. econometrics , finance , sentiment analysis ?

  • @madaraogot5322
    @madaraogot5322 Před 6 lety

    Great information, thanks.

  • @fernandojackson7207
    @fernandojackson7207 Před 6 lety +1

    I also enjoyed and understood well, but I am really craving an actual example

  • @isaackosi2889
    @isaackosi2889 Před 7 lety

    Thanks very much for the insight

  • @adilzia
    @adilzia Před 4 lety

    i like your explanation #CFA

  • @javeda
    @javeda Před 6 lety

    Can our observed exogenous and endogenous variables be continuous and categorical (dichotomous,ordinal, binary) simultaneoulsy, if yes which software is most appropriate for conducting CFA and SEM then alongside moderation and mediation analyses.

  • @barbarabomfim7408
    @barbarabomfim7408 Před 7 lety

    Very informative!

  • @mugomuiruri2313
    @mugomuiruri2313 Před 7 měsíci

    good

  • @sethjchandler
    @sethjchandler Před 11 měsíci

    Perhaps it is just me, but I find it very hard to fully grasp the material without worked examples. Some code or pseudo-code that made the procedures more precise would have been very useful. Everyone has their own learning style, but the one used here does not work for me.

  • @yosefsol8262
    @yosefsol8262 Před 3 lety

    I still don't see why it is required that students have to do SEM thesis, or a thesis at least

  • @nazdezigns31
    @nazdezigns31 Před rokem

    25:00

  • @jonathanstudentkit
    @jonathanstudentkit Před 6 lety

    eh eh eh eh eh eh eh eh eh

    • @shawnmiller6147
      @shawnmiller6147 Před 5 lety +1

      Get a life! If you are so bothered by the eh's then don't watch! Better yet, if you're so damn great, make your own video! I watch the video to learn about SEM, NOT to worry about speech patterns.

    • @DonJonston
      @DonJonston Před 4 lety

      thank you for ruining a very, very helpful video. Be better. Fuck you

  • @laxmanpokhrel2091
    @laxmanpokhrel2091 Před 7 lety

    Remarkably crafted presentation and contents ...Great learning experience...Thank you. ..