Announcement

Collapse
No announcement yet.
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • Data transformation for bacterial count data

    Hello Stata Altruistic,

    In my dataset I have faced some problems with bacterial count data.

    Click image for larger version

Name:	Data_log ESBL problem1.png
Views:	1
Size:	16.5 KB
ID:	1452450


    Here TBX= Total E.coli count, ESBL= Total beta lactamage e.coli count,
    Now i want to work with ESBL proportion (ESBLProp=ESBL/TBX) for further analysis but for 0/0 values corresponding ESBLProp cell remain blank. So in analysis it consider as missing value. I know 0/0= Infinity. To remove these problem i have taken some transformation:

    Code:
    gen logTBX= log10(1+TBX)
    gen logESBL=log10(1+ESBL)
    gen ESBLProp=ESBL/TBX
    gen logESBLProp= log10(ESBLProp)
    gen logESBLProp1= log10(1+ESBLProp)
    gen logESBLProp2= logESBL/logTBX
    gen tESBLProp= asin(sqrt( ESBLProp ))
    gen tESBLProp1= asin(sqrt( ESBL/TBX ))
    My question is
    1. Which transformation is used in these situations? I searched and got above mentioned transformation but need reliable transformation method.
    2. In addition it very much logical if you don't have TBX then you don't have ESBL count as well, what will be steps for further analysis, treat these as missing value or not?
    3. I'm pretty sure I can use GLM, ZIP for ESBL, what will be better choice for dependent variable ESBL or logESBL?
    Last edited by Rayhan Islam; 09 Jul 2018, 00:48.

  • #2
    None of the above. I would consider a poisson of ESBL with TBX as an offset().
    ---------------------------------
    Maarten L. Buis
    University of Konstanz
    Department of history and sociology
    box 40
    78457 Konstanz
    Germany
    http://www.maartenbuis.nl
    ---------------------------------

    Comment


    • #3
      Thanks for your prompt reply. Why none of the above conversion is right choice. Would you please explain.
      For bacterial count data people use log transformation every now and then.

      Comment


      • #4
        See the concurrent thread https://www.statalist.org/forums/for...predict-values

        Comment

        Working...
        X