[R] more on lm(y~x) question: removing NA´s

[Adaikalavan Ramasamy]

1. There should have been warning or error when using "_" as it is
depreceated. Use "<-" instead.
2. There is an extra "]"
3. Could it be that after removing all the cases with NA, you do not
have sufficient observations. Example :

> j <- c(NA, 2, NA,  4, NA)
> k <- c(1, NA,  3, NA,  5)
> lm(j~k,na.action=na.exclude)
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
        0 (non-NA) cases

4. I would suggest you put a 'cat(i, "before", "\n") or something
similar before and after the problematic syntax to find out which values
of i is causing the problem.



On Tue, 2004-05-04 at 14:55, Christoph Scherber wrote:
> actually, the situation is much more complicated. I am producing 
> multiple graphs within a "for" loop. For some strange reason, the 
> plotting routine always stops once lm(y~x) encounters more than one 
> missing value (I have marked the important bit with "***********"):
> 
> par(mfrow=c(5,5))
> p_seq(3,122,2)
> i_0
> k_0
> number_0
> for (i in p) {
>    j_foranalysis[93:174,i+1]
>    k_foranalysis[93:174,i]  
>    df_data.frame(j,k)
>    mainlab1_substring(names(foranalysis[i]),2,8)
>    mainlab2_"; corr.:"
>    mainlab3_round(cor(j,k,na.method="available"),4)
>    mainlab4_"; excl.Mono:"
>    mainlab5_round(cor(j[j<0.9],k[j<0.9],na.method="available"),4)
>    mainlab_paste(mainlab1,mainlab2,mainlab3,mainlab4,mainlab5)
>    plot(k,j,main=mainlab,xlab="% of total biomass",ylab="% of total 
> cover",pch="n")
>    for (k in 1:length(foranalysis[93:174,i])) 
> number[k]_substring(plotcode[foranalysis[k,1]],1,5)
>    text(foranalysis[93:174,i],foranalysis[93:174,i+1],number)
> **********************************
>    model_lm(j~k,na.action=na.exclude])
> **********************************
>    abline(model)
>    abline(0,1,lty=2)
>     }
> 
> Does anyone have any suggestions on this?
> 
> Best regards
> Chris.,
> 
> 
> 
> 
> Liaw, Andy wrote:
> 
> >By (`factory') default that's done for you automagically, because
> >options("na.action") is `na.omit'.
> >
> >If you really want to do it `by hand', and have the data in a data frame,
> >you can use something like:
> >
> >lm(y ~ x, df[complete.cases(df),])
> >
> >HTH,
> >Andy
> >
> >  
> >
> >>From: Christoph Scherber
> >>
> >>Dear all,
> >>
> >>I have a data frame with different numbers of NAÂ´s in each 
> >>column, e.g.:
> >>
> >>x       y  
> >>1      2
> >>NA  3
> >>NA  4
> >>4     NA
> >>1     5
> >>NA NA
> >>
> >>
> >>I now want to do a linear regression on y~x with all the NAÂ´s 
> >>removed. 
> >>The problem now is that is.na(x) (and is.na(y) obviously 
> >>gives vectors 
> >>with different lengths. How could I solve this problem?
> >>
> >>Thank you very much for any help.
> >>
> >>Best regards
> >>Chris
> >>
> >>______________________________________________
> >>R-help at stat.math.ethz.ch mailing list
> >>https://www.stat.math.ethz.ch/mailman/listinfo/r-help
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> >>
> >>
> >>    
> >>
> >
> >
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