Thank you for the suggestion
What seems to work is assigning out_put$Case <- Inp_dat$Case
that is
for(i in 1:4)
{
...
Case<- Inp_dat$Case[i]
…
out_put[i,]<-data.frame(Case, stdL, stdPP, stdSE, L, PP, PP_SE)
}
out_put$Case <- Inp_dat$Case
out_put
What I don't understand i
Apologies I was trying to simplify the programme and missed out four input
files. The files on Andrew, Burt, Charlie and Dave have the same format of
one factor and 13 numeric variables with repeated measurements eg.
Study v1 v2 v3 v4 v5 v6 v7 v8 v9
I am trying to incrementally add rows to an empty data frame. The data has 7
columns, the last 6 are numeric.
For the first columns I would like to include a text identifier, called
‘Case’ like Andrew, Burt, Charlie etc. that is also output to a data frame –
this is where I am having the problem
Thanks, modifying the predict function to allow for new levels was what was
required
Brian
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Hi All,
I need to be able to manipulate the names of the coefficients from
*ranef()*.
If there is any missing data when fitting a mixed model using lmer, no
estimate is returned for the associated level for that random effect. Thus
if the data input for regions had levels
*Region*
HI,
I am using lmer() for a simple mixed effects model. The model is of the form
logit(y)~ x + (1|z), where x is an indicator variable and z a multi-level
factor.
I would like an estimate of the response variable (either y or logit y) with
an associated confidence interval for a given value of x.
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