Data Screening, Cleaning and How to Replace Missing Values in SPSS

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  • Опубликовано: 14 июл 2024
  • The session guides on how to check respondent misconduct using MS Excel. Further, This session discusses in detail missing data and how to replace missing values using the Imputation techniques (Series Mean and Linear Interpolation Method) in SPSS
    For Notes Visit
    researchwithfawad.com/index.p...
    #SPSS #SPSSTutorial #SPSSDataAnalysis #MissingData #SeriesMean #LinearInterpolationMethod #dataanalysis #datacleaning

Комментарии • 33

  • @Junaidkhan-ce4yd
    @Junaidkhan-ce4yd Год назад +1

    Thank you so much for such a nice and clear explanation

  • @Alhamzah_F_Abbas
    @Alhamzah_F_Abbas Год назад +1

    Great explanation. well done

  • @talhamansoor7108
    @talhamansoor7108 2 года назад +1

    That's great

  • @gentesipam3895
    @gentesipam3895 5 месяцев назад +1

    thank you so much

  • @480sachin
    @480sachin 2 года назад +1

    EXCELLENT SIR

  • @HaPham-fq1xt
    @HaPham-fq1xt Год назад

    Thank you so much for the great explanation. However, you mentioned that the data should be removed if a standard deviation is under .25. Is that any reference for it?

    • @researchwithfawad
      @researchwithfawad  Год назад

      Thanks. I am glad you liked it. You may refer to
      Collier, J. E. (2020). Applied structural equation modeling using AMOS: Basic to advanced techniques. Routledge.

  • @alexanderstevens2077
    @alexanderstevens2077 Год назад

    Also, would you recommend examing missing values on a case-by-case basis for missing items that may have been unintentionally skipped by a respondend? It seems to me that, for variables missing > 10% doing this would allow the researcher to determine if, due to some factor, the respondent unintentionally skipped it and directly fill in the best possible value

    • @researchwithfawad
      @researchwithfawad  Год назад +1

      Yes, you can perform that imputation and there is also support in the literature for it.

  • @alexanderstevens2077
    @alexanderstevens2077 Год назад

    Can you please include a video on using Expectation Maximization for data imputation?

  • @alexanderstevens2077
    @alexanderstevens2077 Год назад +1

    Unengaged respondents are those that answer all the same values or does so in patterns such as 1111, 3333, 2222, 4444, and so on. How do you detect those?

    • @researchwithfawad
      @researchwithfawad  Год назад

      Thanks for your comment. One way to do it is to take Standard Deviation of individual constructs for each respondents. Hope this helps.

  • @reisterantiporta9767
    @reisterantiporta9767 Год назад

    Hello! Is it okay if I categorize Likert scale responses as ordinal in SPSS? Or should I categorize it as scale?

    • @researchwithfawad
      @researchwithfawad  Год назад

      The categorization in SPSS doesnt affect the results. You can put them as ordinal or scale.

  • @amalwijenayaka410
    @amalwijenayaka410 Год назад

    Dear Prof: you mentioned that the data should be removed if a standard deviation is under .25. Is there any reference? We have no access to read this book. (Applied structural equation modeling using AMOS: Basic to advanced techniques) That is why?

    • @researchwithfawad
      @researchwithfawad  Год назад +1

      Thanks for your interest. That book is the reference. You can quote the book.

  • @mansour6629
    @mansour6629 3 месяца назад

    Thanks for the great video!
    Could Mode be as well used to replace missing data?

    • @researchwithfawad
      @researchwithfawad  3 месяца назад

      Are you trying to replace the demographics? They should not be replaced.

    • @mansour6629
      @mansour6629 3 месяца назад

      @@researchwithfawad No, sir. There are some missing values in likert scale data. Is Mode an appropriate technique to deal with them?

    • @researchwithfawad
      @researchwithfawad  3 месяца назад

      No.

    • @mansour6629
      @mansour6629 3 месяца назад

      @ResearchWithFawad Thanks!
      Could you please provide a good reference for full guidance on data screening?

    • @researchwithfawad
      @researchwithfawad  3 месяца назад +1

      You may refer to
      Collier, J. (2020). Applied structural equation modeling using AMOS: Basic to advanced techniques. Routledge.

  • @saminazaidiacademy8219
    @saminazaidiacademy8219 10 месяцев назад

    How to put multivariables into one variable for data analysis..like 5 items are showing results of one dimensions so how can i analyze

    • @researchwithfawad
      @researchwithfawad  10 месяцев назад +1

      Thanks for your interest.
      You will need to take the sum of the individual items. Let say, i have Organizational Commitment measured using 4 items COM1, COM2, COM3, COM4
      If you have it in SPSS,
      Go to Transform -> Compute Variable
      In the Target Variable Enter the Name of the New Variable that is to be created based on taking the average, let say COMM.
      In the numeric expression type in
      Mean(COM1, COM2, COM3, COM4)
      Press OK. The new variable is created at the end of the Data View and is also visit in the variable view. You have now composite score for each respondent that you can use in regression.

    • @saminazaidiacademy8219
      @saminazaidiacademy8219 10 месяцев назад

      @@researchwithfawad thanks for your timely reply🙏
      I have 5 items in.each COM1 ,COM2 ,COM3...Then how to compute them....to make it one COMM

  • @areegtooba8260
    @areegtooba8260 6 месяцев назад

    If we added the new column due to imputation. Now may we delete the previous one which was with missing value? How we will use this new one in applying any test?

    • @researchwithfawad
      @researchwithfawad  6 месяцев назад +1

      Use he newly formed variable. You can keep the old one but not use it for further analysis