A model for repeated treatments and repeated outcomes
Dear Dan, You'll need to provide more information. What is the global pattern that you expect (linear? quadratic? non-linear?) How to you thing that the operation can effect the GFR? You need to answer those kind of questions so that you can make a sensible fixed effects part of the model. The random effect is probably just ~1|Patient. And a corCAR1(form = ~ Time) can handle the temporal correlation within the patient. Best regards, ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey 2016-02-09 0:55 GMT+01:00 Daniel Rubi via R-sig-mixed-models < r-sig-mixed-models at r-project.org>:
I have the following experimental design:Measurements of kidney function
(in units called GFR) taken at several time points pre-operation (time
points not evenly spaced) and at several time points post-operation
(neither evenly spaced).
Here's an example of my data in R code:
set.seed(1)df <- data.frame(patient = letters[1:10],
gfr_ten_days_prop = rnorm(10,5,1), gfr_five_days_prop = rnorm(10,10,1),
gfr_three_days_prop = rnorm(10,12,1), gfr_one_day_postop =
rnorm(10,10,1), gfr_one_day_postop = rnorm(10,5,1), gfr_one_day_postop =
rnorm(10,2,1))
I'm looking for a model which will estimate the effect of pre-operation
GFR on post-operation GFR, taking into account the different times at which
GFRs were measured pre- and post-operation.One additional possible caveat -
my data contain missing values (NAs).
I'm having a hard time seeing how a mixed-effects model fits this problem
since in all the examples of repeated measures/longitudinal data I came
across in each time point the response is measured whereas here it is more
a predictive question - how strong does each pre-operation GFR predict
pos-operation GFR, where the time at which GFRs were measured may matter.
Thanks a lot,Dan
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