+ Reply to Thread
Results 1 to 3 of 3

Thread: Combining data from different sources

  1. #1
    Points: 2,462, Level: 30
    Level completed: 8%, Points required for next Level: 138

    Posts
    200
    Thanks
    20
    Thanked 48 Times in 43 Posts

    Combining data from different sources




    Hi,

    I have data from two very different sources (bird counts from ships and bird counts from the shore) which aim to estimate the same population/outcome. Both data have different covariates/predictors and thus it is difficult to combine both data in the same regression model.

    Does somebody know which methods exist to combine both data in order to estimate the same outcome? I know a little bit about model averaging / machine learning techniques, but are there alternatives? I would really like to use both data within the same model.

    Thanks!

  2. #2
    Omega Contributor
    Points: 38,432, Level: 100
    Level completed: 0%, Points required for next Level: 0
    hlsmith's Avatar
    Location
    Not Ames, IA
    Posts
    7,006
    Thanks
    398
    Thanked 1,186 Times in 1,147 Posts

    Re: Combining data from different sources

    I think there are test to compare the outcomes, but combining them would leave a lot of missing data, right??
    Stop cowardice, ban guns!

  3. #3
    Points: 2,462, Level: 30
    Level completed: 8%, Points required for next Level: 138

    Posts
    200
    Thanks
    20
    Thanked 48 Times in 43 Posts

    Re: Combining data from different sources


    Yes, I mean assume that we have two different counting methods, both with outcome "N", and the variable "Year" in order to estimate the trend of "N". And now we have two distinctly different covariates, each covariate corrects for a certain bias produced with each counting method, let's say "X" and "Y". If I just combine all data in a dataframe, I have always one missing value in each row (either for X or for Y), so no data would be used within the regression. However, I would like to use the data from both sources simultaneously to have a more precise trend estimate and to increase the power of the regression analysis.

+ Reply to Thread

           




Tags for this Thread

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