Meta-analysis 101: What, Why, and How

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  • เผยแพร่เมื่อ 14 พ.ย. 2024

ความคิดเห็น • 18

  • @marcelolarrea4583
    @marcelolarrea4583 ปีที่แล้ว +1

    It was really helpful .....thanks a lot.

  • @kanzarauf880
    @kanzarauf880 3 ปีที่แล้ว +3

    sir. can you kindly share the slides or the last slide with websites. and thank you for this comprehensive vides. really helpful.

    • @saeedsharif
      @saeedsharif  3 ปีที่แล้ว

      Hi Kanza, you should contact Dr Hassam for the slides. hassamwaheed92@gmail.com

  • @solutionsplatforms5439
    @solutionsplatforms5439 2 ปีที่แล้ว

    Great presentation. Please can anyone help with this PowerPoint? Thank you in advance

  • @dr.brigchandrasekharb7004
    @dr.brigchandrasekharb7004 2 ปีที่แล้ว

    Very Nice Webinar, Highly informative, Dr Sayeed
    Is it possible to have these slides please, especially the Coding Manual slide is not visible properly, (to note down)

    • @hassamwaheed8967
      @hassamwaheed8967 2 ปีที่แล้ว +1

      Hi, the slides are available on my researchgate profile. Many thanks.

    • @fenetbelay2251
      @fenetbelay2251 2 ปีที่แล้ว

      Hello Dr. Hassam. I found your presentation is too helpful. Thank you!

  • @maroofmaroof3799
    @maroofmaroof3799 3 ปีที่แล้ว +2

    Respected Sir can you kindly share the PowerPoint presentation?

    • @saeedsharif
      @saeedsharif  3 ปีที่แล้ว

      Sorry for the late response. You should contact Dr Hassam at hassamwaheed92@gmail.com

    • @burakylcnygt
      @burakylcnygt 3 ปีที่แล้ว +1

      Mr Maroof, if you got your e-mail, could you send it to me?

    • @maroofmaroof3799
      @maroofmaroof3799 3 ปีที่แล้ว

      @@burakylcnygt dear I dont have the presentation but you can connect with Hassam on fb or through email.He will help you hopefully.

  • @saeedewu129
    @saeedewu129 2 ปีที่แล้ว

    Great. But what is the total effect size? is it the summation of multiplication of inverse variance and fisher z of all the studies?

    • @hassamwaheed8967
      @hassamwaheed8967 2 ปีที่แล้ว

      The average effect size is simply the statistical aggregation of the extracted effect sizes weighed against the inverse of variance. Inverse-variance weighting is done to ensure that studies that have larger sample sizes and by default, lower standard errors are given greater weightage to the average effect size. You will have to define the model to aggregate the effect sizes as either a fixed effects model or a random effects model. Under a fixed effects model, one true effect size is assumed and differences in effect sizes is attributed to sampling error. Under a random effects model, the true effect size is allowed to differ and heterogeneity in effect sizes is often attributed to study characteristics (i.e., the moderators).

    • @saeedewu129
      @saeedewu129 2 ปีที่แล้ว

      @@hassamwaheed8967 thanks a lot for the clarification about the average effect size. Just another small question, in the summary result (R Metaphor ), the estimate (0.1795), is the same as the average effect size you just said?

  • @bijoydey479
    @bijoydey479 3 ปีที่แล้ว

    Sir, I have more than 10 moderator...and also publication bias..how do run meta regression.. please guide me..thq u

  • @UdayKiranKommuriPHD
    @UdayKiranKommuriPHD 3 ปีที่แล้ว

    Sir, for meta-analysis, do we have to follow the PRISMA framework. How to collect the data and what methods can be used to write the data. is it the same as systematic review, where we include all the data in excel or do we need to adopt any software?. kindly Guide Sir.
    Sir, I am very thankful for your Guidance for systematic review. I have followed the steps as given in the video and submitted it for publication.

  • @animinarni1602
    @animinarni1602 3 ปีที่แล้ว

    The topic you present is very interesting. In this regard, I have sent a message to your fb. Please respond. Tks

    • @saeedsharif
      @saeedsharif  3 ปีที่แล้ว

      Thank you for the comment. To my fb or Hassam's fb?