+ Reply to Thread
Page 2 of 2 FirstFirst 1 2
Results 16 to 18 of 18

Thread: Skew in data

  1. #16
    Fortran must die
    Points: 58,790, Level: 100
    Level completed: 0%, Points required for next Level: 0
    noetsi's Avatar
    Posts
    6,532
    Thanks
    692
    Thanked 915 Times in 874 Posts

    Re: Skew in data




    The more I read today the less serious violations of assumptions appear if you have large data sets. So my question is, why do so many text stress strongly the danger of violating the assumptions and the need for strict test of this?

    I assume it is because its common not to have data sets with thousands of records in academic research

    I spent a lot of time in the last few years learning how to capture and correct violations of methods specifically because of the concern raised....
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

  2. #17
    Devorador de queso
    Points: 95,922, Level: 100
    Level completed: 0%, Points required for next Level: 0
    Awards:
    Posting AwardCommunity AwardDiscussion EnderFrequent Poster
    Dason's Avatar
    Location
    Tampa, FL
    Posts
    12,937
    Thanks
    307
    Thanked 2,630 Times in 2,246 Posts

    Re: Skew in data

    It's better to have people concerned about the assumptions even if they might not be necessary in every single case than it is to have people blindly ignore the assumptions all the time.
    I don't have emotions and sometimes that makes me very sad.

  3. #18
    Fortran must die
    Points: 58,790, Level: 100
    Level completed: 0%, Points required for next Level: 0
    noetsi's Avatar
    Posts
    6,532
    Thanks
    692
    Thanked 915 Times in 874 Posts

    Re: Skew in data


    Quote Originally Posted by Dason View Post
    It's better to have people concerned about the assumptions even if they might not be necessary in every single case than it is to have people blindly ignore the assumptions all the time.
    I am sure that is true. Of course there are outliers like me so paranoid about making "mistakes" by violating assumptions that he is reluctant to send anything in

    One thing I had not thought of is that many of the alternatives, such as robust methods, have assumptions themselves that when violated can create significant issues. And transformations, which in my case did not work well although I used most of the ones recommended, have serious issues. First, its hard to interpret the results of the transformed variables and 2nd) in changing the distribution of the data they can distort the results [especially if you are not careful which one to use, but to some extent always}. This is particularly true with data that has lots of 0's and negative numbers which my data always has.
    "Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995

+ Reply to Thread
Page 2 of 2 FirstFirst 1 2

           




Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts






Advertise on Talk Stats