Displaying 2 results from an estimated 2 matches for "obese14".
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2013 Jan 06
4
random effects model
Hi A.K
Regarding my question on comparing normal/ obese/overweight with blood
pressure change, I did finally as per the first suggestion of stacking the
data and creating a normal category . This only gives me a obese not obese
14, but when I did with the wide format hoping to get a
obese14,normal14,overweight 14 Vs hibp 21, i could not complete any of the
models.
This time I classified obese=1 & overweight=1 as obese itself.
Can you tell me if I can use the geese or geeglm function with this data
eg: : HIBP~ time* Age
Here age is a factor with 3 levels, time: 2 levels, HIBP = ye...
2012 Dec 28
3
help with reshaping wide to long format
...0 = c(4L, 3L, 6L, 6L, 4L, 6L, 3L, 4L,
> 4L, 4L, 4L, 4L, 4L), ra98 = c(1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
> 2L, 2L, 2L, 3L, 1L), CBCLAggressionAt1410 = c(NA, 0L, NA, 0L,
> 0L, 0L, NA, 0L, NA, NA, 0L, 0L, NA), CBCLInternalisingAt1410 = c(NA,
> 0L, NA, 0L, 0L, 0L, NA, 0L, NA, NA, 0L, 0L, NA), Obese14 = c(NA,
> 0L, NA, 0L, 0L, 0L, NA, NA, NA, NA, 0L, 0L, NA), Obese21 = c(NA,
> 0L, NA, 1L, 0L, 0L, NA, 0L, NA, NA, 0L, 0L, NA), Overweight14 = c(NA,
> 0L, NA, 0L, 0L, 0L, NA, NA, NA, NA, 0L, 0L, NA), Overweight21 = c(NA,
> 1L, NA, 1L, 0L, 0L, NA, 0L, NA, NA, 1L, 0L, NA), hibp14 = c(NA,
&g...