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I've got repeated measurements data in which patients are measured an irregular amount of times (2 through 6 times per patient) and also with unequally spaced time intervals (some subsequent measures are 6 months apart, some 3 years). Is it possible to model this in a GEE model? For example by specifying a continuous AR1 correlation structure?

I've got some example data:

library(tidyverse)
library(magrittr)
library(geepack)
library(broom)

example_data <- structure(list(pat_id = c(2, 2, 2, 2, 2, 2, 3, 3, 4, 4, 4, 4, 
4, 7, 7, 8, 8, 8, 13, 13), measurement_number = c(1L, 2L, 3L, 
4L, 5L, 6L, 1L, 2L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 1L, 2L, 3L, 1L, 
2L), time = c(0, 0.545, 2.168, 2.68, 3.184, 5.695, 0, 1.892, 
0, 0.939, 1.451, 1.955, 4.353, 0, 4.449, 0, 0.465, 4.005, 0, 
0.364), age_standardized = c(-0.0941625479695087, -0.0941625479695087, 
-0.0941625479695087, -0.0941625479695087, -0.0941625479695087, 
-0.0941625479695087, -1.76464003778333, -1.76464003778333, -0.667610044472762, 
-0.667610044472762, -0.667610044472762, -0.667610044472762, -0.667610044472762, 
0.142696200586183, 0.142696200586183, 0.00556745142236116, 0.00556745142236116, 
0.00556745142236116, 0.0554324511182961, 0.0554324511182961), 
    sex = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
    2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Female", 
    "Male"), class = "factor"), outcome = c(4241.943359375, 4456.4, 
    6533.673242397, 7255.561628906, 7594.527875667, 6416.4, 373.782029756049, 
    614.318359374, 6675.19041238403, 10623.94276368, 10849.01013281, 
    10627.30859375, 13213, 541.40780090332, 2849.5551411438, 
    2136.2, 2098.1, 2063.9, 5753.56313232422, 5108.199752386)), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -20L))

head(example_data)
# A tibble: 6 x 6
  pat_id measurement_number  time age_standardized sex    outcome
   <dbl>              <int> <dbl>            <dbl> <fct>    <dbl>
1      2                  1 0              -0.0942 Female   4242.
2      2                  2 0.545          -0.0942 Female   4456.
3      2                  3 2.17           -0.0942 Female   6534.
4      2                  4 2.68           -0.0942 Female   7256.
5      2                  5 3.18           -0.0942 Female   7595.
6      2                  6 5.70           -0.0942 Female   6416.

I actually have also modelled these data with a linear mixed model (using nlme specifying a continuous AR1), but my supervisor asked me to also explore using a GEE, thats why I ask. I've read that, using the geepack package, it is possible to define the correlation structure yourself, but I can't code that well to see if it is possible to define the structure so that rho is adjusted for the time interval in between measurements (by making it rho^s where s is the number of time units).

tcvdb1992
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  • do you want an ar1 structure? or what you describe later? – SushiChef Dec 15 '21 at 14:21
  • Hi @SushiChef, I specifically am trying to model a *continuous* AR1 structure. I'm not sure if thats a widely used term, so later on I specify that what I mean by this is that the rho from the traditional AR1 structure is adjusted for the time interval between two subsequent measurements. I've specified the continuous correlation structure in my mixed model by adding `correlation=corCAR1(form=~1|id)`, but I was not sure if a similar procedure is available for GEE, hence my question. – tcvdb1992 Dec 16 '21 at 10:24

0 Answers0