[R-sig-ME] Creating a for loop for a mixed-effects model with covariates
@hm@dr215 m@iii@g oii tpg@com@@u
@hm@dr215 m@iii@g oii tpg@com@@u
Wed Jul 10 10:44:22 CEST 2019
Hi
This is a repeated measures data, and I would like to use a mixed-effects
model to run this. The model includes; independent variables (e.g. ADRB2),
groups (GID), Time, and covariates (e.g. ADRB2_pre) and IDs for the repeated
measures (see below, the dataset). I have 59 variables (independent
variables) with 59 covariates (one for each independent variable). The
covariates are pre_treatment values.
I am trying to use a "for loop" to run this for 59 variables and covariates
(pre-treatment values). There are two variables that will change in each
model in the loop (see below), how can I make a loop to different these two?
e.g.
1) ADRB2: if this could be [i]; 2) ADRB2_pre (pre_treatment): is a covariate
(i+1) for variable ADRB2, not sure how this should be looped?
These two variables are listed next to each other (i & i+1) in the
spreadsheet, how I can loop the second one (i+1) as a covariate in the
model? I then need to move to other variables (59 of them) in a loop, and so
on..
Below is a subset of my data, I have 6 groups with 4 subjects within each
group.
Your help would be greatly appreciated.
I looked at the examples on the web, none of those that I found is similar
to what I intend to do. I was able to make a simple loop for the independent
variable, not for the covariates; and didn't work for 59 variables.
# This is my codes for a simple model
dat <- read.csv("ct_data.csv", header = TRUE, sep=",", na.strings = NA)
# exclude Time 0 form the dataset
dat1 <- subset(dat, Time >0 , select=1:121)
# factors
dat1$GID <- factor(dat1$GID); dat1$Time <- factor(dat1$Time)
library(nlme);
#Mixed-effects model
model <- lme(ADRB2 ~ GID + Time + ADRB2_pre, data = dat, random = ~ 1 | ID)
summary(model)
Repeats
Time
Groups
Independent var_1
Covariate_var1
Independent var_2
Covariate_var2
ID
Time
GID
ADRB2
ADRB2_pre
ACE
ACE_pre
1
0
0
21.58
21.58
21.58
21.58
2
0
0
20.05
20.05
20.05
20.05
3
0
0
21.49
21.49
21.49
21.49
4
0
0
22.08
22.08
22.08
22.08
5
0
1
21.31
21.31
21.31
21.31
6
0
1
20.92
20.92
20.92
20.92
7
0
1
21.21
21.21
21.21
21.21
8
0
1
21.54
21.54
21.54
21.54
9
0
2
20.07
20.07
20.07
20.07
10
0
2
20.66
20.66
20.66
20.66
11
0
2
21.46
21.46
21.46
21.46
12
0
2
21.81
21.81
21.81
21.81
13
0
3
20.08
20.08
20.08
20.08
14
0
3
21.27
21.27
21.27
21.27
15
0
3
21.94
21.94
21.94
21.94
16
0
3
20.8
20.8
20.8
20.8
17
0
4
21.1
21.1
21.1
21.1
18
0
4
20.33
20.33
10.54
10.54
19
0
4
21.55
21.55
21.55
21.55
20
0
4
21.28
21.28
21.28
21.28
21
0
5
20.54
20.54
20.54
20.54
22
0
5
20.69
20.69
20.69
20.69
23
0
5
20.87
20.87
20.87
20.87
24
0
5
22.02
22.02
22.02
22.02
1
1
0
21.56
21.58
21.56
21.58
2
1
0
20.12
20.05
20.12
20.05
3
1
0
21.71
21.49
21.71
21.49
4
1
0
20.77
22.08
20.77
22.08
5
1
1
21.1
21.31
21.1
21.31
6
1
1
21.09
20.92
21.09
20.92
7
1
1
21.05
21.21
21.05
21.21
8
1
1
21.4
21.54
21.4
21.54
9
1
2
19.89
20.07
19.89
20.07
10
1
2
20.93
20.66
20.93
20.66
11
1
2
21.72
21.46
21.72
21.46
12
1
2
21.11
21.81
21.11
21.81
13
1
3
22.1
20.08
22.1
20.08
14
1
3
21.14
21.27
21.14
21.27
15
1
3
20.7
21.94
20.7
21.94
16
1
3
20.98
20.8
20.98
20.8
17
1
4
20.75
21.1
20.75
21.1
18
1
4
20.88
20.33
20.88
10.54
19
1
4
21.19
21.55
21.19
21.55
20
1
4
20.48
21.28
20.48
21.28
21
1
5
20.55
20.54
20.55
20.54
22
1
5
21.77
20.69
21.77
20.69
23
1
5
21.2
20.87
21.2
20.87
24
1
5
20.12
22.02
20.12
22.02
1
2
0
22.45
21.58
22.45
21.58
2
2
0
17.83
20.05
17.83
20.05
3
2
0
21.26
21.49
21.26
21.49
4
2
0
20.69
22.08
20.69
22.08
5
2
1
21.73
21.31
21.73
21.31
6
2
1
22.16
20.92
22.16
20.92
7
2
1
20.85
21.21
20.85
21.21
8
2
1
21.58
21.54
21.58
21.54
9
2
2
22.34
20.07
22.34
20.07
10
2
2
20.91
20.66
20.91
20.66
11
2
2
20.22
21.46
20.22
21.46
12
2
2
21.24
21.81
21.24
21.81
13
2
3
21.18
20.08
21.18
20.08
14
2
3
21.74
21.27
21.74
21.27
15
2
3
20.8
21.94
20.8
21.94
16
2
3
21.71
20.8
11.16
20.8
17
2
4
21.6
21.1
21.6
21.1
18
2
4
19.06
20.33
8.98
10.54
19
2
4
21.26
21.55
21.26
21.55
20
2
4
21.87
21.28
21.87
21.28
21
2
5
20.82
20.54
20.82
20.54
22
2
5
21.1
20.69
21.1
20.69
23
2
5
21.09
20.87
21.09
20.87
24
2
5
20.03
22.02
20.03
22.02
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