On Jul 11, 2011, at 11:51 AM, Meesters, Christian wrote:
Hi,
I would like to tabulate the likelihood for an affection. For this,
I retrieve indices of affected people and controls for my data set
and proceed as follows:
flags <- c(rep(1, length(patient_indices)), rep(0,
length(control_indices)))
# dataset is a data.frame and param the parameter to be analysed:
data1 <- dataset[,param][c(patient_indices, control_indices)]
fit1 <- glm(flags ~ data1, family = binomial)
new.data <- seq(0, 300, 10)
new.p <- predict(fit1, data.frame(newdata = new.data), type =
"response")
Should (probably) have been ... names of RHS variables need to be
exact match:
new.p <- predict(fit1, newdata= data.frame(data1 = new.data), type =
"response")
(Obviously untested.)
Which than gives data not in dependence of new.data and a warning
which reads
"Warning message:
'newdata' had 31 rows but variable(s) found have 306 rows"
In a similar script new.p were data ranging from 1 to 31 with the
cumulative likelihood associated with them. Now new.p looks a bit
like random numbers assigned to a list ranging from 1 to 306. (306
is the number of datapoints in data1.) Unfortunately I am unable to
spot the difference of the two scripts.
I would appreciate any pointer on my mistake (and hope that my
problem was understandable).
TIA
Christian
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David Winsemius, MD
West Hartford, CT
______________________________________________
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and provide commented, minimal, self-contained, reproducible code.
