ertension correlated in any way or are
> they independent (correlation=0)?
> Are the correlations large enough to adversely influence your model?
> Tim
>
> -Original Message-
> From: R-help On Behalf Of anteneh asmare
> Sent: Wednesday, June 15, 2022 7:29 AM
> To: r
coord_flip() +
>theme_bw()
>
>
> Hope this helps,
>
> Rui Barradas
>
> Às 08:15 de 15/06/2022, anteneh asmare escreveu:
>> Dear Rui, thanks a lot, dose it possible to have the horizontal line
>> for scale OR value on Y axis and different color for entir
le = 90))
> points(OR ~ seq_along(id), ORCI, pch = 16)
> axis(1, at = seq_along(ORCI$id), labels = ORCI$id)
>
>
>
> 2. Package ggplot2
>
>
> library(ggplot2)
>
> ggplot(ORCI, aes(id, OR)) +
>geom_errorbar(aes(ymin = `2.5 %`, max = `97.5 %`)) +
>geom_p
sample_data =
read.table("http://freakonometrics.free.fr/db.txt",header=TRUE,sep=";";)
head(sample_data)
model = glm(Y~0+X1+X2+X3,family=binomial,data=sample_data)
summary(model)
exp(coef(model ))
exp(cbind(OR = coef(model ), confint(model )))
I have the aove sample data on logistic regression wit
lt;- as.data.frame(ID_names2)
> colnames(ID6)<-"val"
> rbind(ID5, ID6)
>
> This works for the first two, just keep doing the same thing for the
> others.
> Tim
>
> -Original Message-
> From: R-help On Behalf Of anteneh asmare
> Sent: Monday, Ju
Now with a simple command we get the desired multiplication
datfm[, (new_ID_names) := .SD *BETA, .SDcols = ID_names]
datfm
str(datfm)
# The PRS for each individual can be calculated using the colSums
function in base R:
PRS<-Dfm1[, colSums(.SD), .SDcols = new_ID_names]
PRS
On 6/13/22, a
between df1 and df2
> # here I have looped through the rows
> nrows<-dim(dfnew)[1]
> idcols<-4:8
> XAcols<-2:3
> for(i in 1:nrows) {
> if(reversals[i]) {
> dfnew[i,XAcols]<-rev(dfnew[i,XAcols])
> dfnew[i,idcols]<-maxid-dfnew[i,idcols]
> }
> }
>
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