[R-lang] Re: How to handle missing data when I try to log-transform my data

[Alex Fine]

*Somewhat timidly in my first response to this list*....I routinely do 
the same thing with spr data--remove RTs below 100ms and above 
2000ms--and do not replace the missing values with anything.  If you 
have some reason to replace the missing values (maybe if you're doing 
ANOVA and want equal numbers of observations in all conditions), maybe 
you could replace them with something very small, e.g. .0001,...but 
doesn't that defeat the purpose of removing abnormally low RTs?  (i.e. 
you're replacing weirdly low RTs with even lower RTs.)  I would 
recommend just removing them and analyzing them with a method that isn't 
so sensitive to the removal (I always use lmer()....)

Xiao He wrote:
> Dear R-lang users
>
> I have a question that is, I suppose, less related to the use of R.
>
> I have a set of self-paced reading data, and all the RTs that are 
> below 100ms are to be discarded. What I used to do when analyzing raw 
> data was to replace discarded values with 0. That was all simple and 
> easy. But I recently started to analyze log-transformed data. An issue 
> then arises as to how to handle missing data. Obviously, if I replace 
> the discarded raw data points with 0, log transformation does not 
> work, as it will return "-Inf" for obvious reasons. So I would like to 
> know what you would suggest me to do in my case. Thank you very much 
> in advance.
>
>
>
> Xiao He
>