[R-sig-ME] adding a constant to a continuous dataset with zero values- to use the log transformation
Thierry Onkelinx
thierry.onkelinx at inbo.be
Tue Apr 3 12:05:15 CEST 2018
Dear Ahmad,
Don't do log(x+1). If you want to see why, then to the analysis with
log(x+1), log(x+100), log(x+0.001), ... and compare the results.
What is causing the zeros? Are they non-detects? Then you need threat
this as censored data (see the NADA package). If they are not, then a
zero-inflated gamma distribution might be an option.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be
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2018-04-03 11:42 GMT+02:00 Ahmad <ahmadr215 at tpg.com.au>:
> Hi all
>
> My question here is related to my previous query on Geometric mean of log
> data.
> I have a continuous dataset with considerable number of zero values, and
> not-normally distributed. Because of zero values, I won't be able to take
> the log of this variable. It has been suggested by some to add a constant
> (e.g. +1) to all data to be able to take the log of data. I can then
> transform back the output of lm() or Mixed-model to the original scale using
> exp() or emmeans function with "response" method as suggested by Russell
> (russell-lenth at uiowa.edu).
>
> I searched this (adding a constant) and found that views on this approach
> are not consistent- I would like to see if anyone has experience on how to
> deal with such data.
>
> Your help is greatly appreciated!
>
> Ahmad
>
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