26. SEMinR Lecture Series - Moderation Analysis in R

Поделиться
HTML-код
  • Опубликовано: 18 сен 2024

Комментарии • 18

  • @aniyebcha7488
    @aniyebcha7488 2 года назад +1

    great discussion and its healpfull

  • @Alhamzah_F_Abbas
    @Alhamzah_F_Abbas Год назад +1

    Great explination

  • @SaraCristinaValenzuelaValenzue

    Hi, first of all, thank you for your videos. They are very helpful, easy to understand and replicate. I have a question regarding a model with two moderation variables that moderate the relationship between the IV and the DV and also include a mediation variable between them. How can I specify and evaluate the model in this particular case?
    Big Data Analytics Capabilities (IV) -> Decision-Making Process (Mediating variable) -> Financial Firm Performance (DV)
    Thanks in advance

    • @researchwithfawad
      @researchwithfawad  Год назад +1

      Thanks for your email and interest. If there are two moderating variables, the process remains the same, link the moderator to the DV of the relationship it moderates, plus the interaction term is also linked to the DV of the relationship.

    • @SaraCristinaValenzuelaValenzue
      @SaraCristinaValenzuelaValenzue Год назад

      @@researchwithfawad Thank you!!

  • @YanboZhang-im4le
    @YanboZhang-im4le 4 месяца назад

    There is no missing data in my dataset, and I think the R package and coding are no problem. However, I encountered error issues repeatedly. The following is my code and error information. Please help me with this problem! Many thanks.
    **Coding: **
    # Create measurement model
    mm_1

  • @estevanharyanto2981
    @estevanharyanto2981 2 года назад

    Hi, I am wondering how I can apply the interaction term in a model consisting of more than 1 independent variable (i.e. 4 IVs). For instance, initial model: Y = x1 + x2 + x3 + x4 + e; however, I want to apply an interaction term ('x5') that applies for each of the stated independent variable. So, Y = x1 + x2 + x3 + x4 + x5 + x1*x5 + x2*x5 .. x4*x5 + e. How would you compute that on R? How would my measurement model and structural model should look like?

    • @researchwithfawad
      @researchwithfawad  2 года назад

      Thanks for your query. Even if you have more than 1 IV, the process remains the same. You have to create separate interaction term for each moderator with the IV.
      In order to make it simpler, For Measurement mode, you do not need to create interaction terms. You can do it separately for the structural model.
      You can post your code on the FB group or email me kh.fawad83@gmail.com in case there is any issue.

  • @Shubiduba
    @Shubiduba Год назад

    Hi, great explanation! But here don't work:
    Error in moderated_model$path_coef[c(iv, paste(iv, "*", moderator, sep = ""), :
    subscript out of bounds

    • @researchwithfawad
      @researchwithfawad  Год назад

      Can you post the error, with screenshot of the code on the facebook group. SEMinR

  • @shadeel9293
    @shadeel9293 2 года назад

    Dear sir, thank you so much for your informative videos. Sir, please guide me. How will we create a measurement model and estimate the model when we have three mediating variables? When I run the estimate the model step I got this error"Error in first_stage$construct_scores[, iv] : subscript out of bounds". Thank you

    • @researchwithfawad
      @researchwithfawad  2 года назад

      Here is the video for the multiple mediators
      ruclips.net/video/1lYMAVqmUUE/видео.html

    • @shadeel9293
      @shadeel9293 2 года назад

      @@researchwithfawad if we have more than one iv, how we will do moderation analysis?

    • @researchwithfawad
      @researchwithfawad  2 года назад +1

      The approach remains the same. You will need to add more relationship as done in other videos in the SEMinR playlist.

    • @shadeel9293
      @shadeel9293 2 года назад

      @@researchwithfawad Dear Sir Thank you so much for your speedy response every time. Sir if we have three mediating variables, can we analyze them one by one ? or will we analyze those three once?