Hi all,

Our dataset is a repeated measures design including 3 groups (a) Controls,
(b) Small stroke and (c) Large stroke. We want to know if the group behave
different over time.

We first fitted a lme with fixed = group * time (see below).
Their was a significant interaction effect (see below as well; p < 0.05)

In the next step we want to know which groups have significant interactions
(Control - Stroke large, Control - Stroke small, Stroke small - Stroke
large), and their p-values + CIs.

A posthoc Tukey, I think is fine. However, I do not know how to setup the
constrast matrix.

These are the contrast names ( names( coef( model ) ) ):
"(Intercept)", "groupStroke large", "groupStroke small", "time",
"groupStroke large:time" "groupStroke small:time"

I guess, the model has to be refitted to get a contrast for
"groupControl:time" as well, but I do not know how.

Any solution known? (Probabily something in the direction of: model.2 <-
update( model, fixed = 0 + group * time ) )

Thanks!

Chris





This is a print of the dataset:

    subject        group       value day
1       N03 Stroke small  0.47545500   0
2       N04 Stroke small  0.38866500   0
3       N19 Stroke small  0.64749800   0
4       N20 Stroke small  0.50468600   0
5       N22 Stroke small  0.55872300   0
6       N03 Stroke small  0.01979970   3
7       N04 Stroke small  0.05607250   3
8       N19 Stroke small -0.04506370   3
9       N20 Stroke small -0.33935400   3
10      N22 Stroke small  0.22052700   3
11      N03 Stroke small  0.29805300   7
12      N04 Stroke small -0.24908100   7
13      N19 Stroke small -0.02657290   7
14      N20 Stroke small -0.19483200   7
15      N22 Stroke small  0.50948000   7
16      N03 Stroke small  0.13056600  21
17      N04 Stroke small  0.33759500  21
18      N19 Stroke small  0.14929200  21
19      N20 Stroke small  0.25033100  21
20      N22 Stroke small  0.71456800  21
21      N03 Stroke small  0.39007100  49
22      N04 Stroke small  0.33254400  49
23      N19 Stroke small  0.27767600  49
24      N20 Stroke small  0.33467500  49
25      N22 Stroke small  0.52203500  49
26      N03 Stroke small  0.29851100  70
27      N04 Stroke small  0.50900200  70
28      N19 Stroke small  0.51781700  70
29      N20 Stroke small  0.69543700  70
30      N22 Stroke small  0.49337000  70
31      N01 Stroke large          NA   0
32      N07 Stroke large  0.54930600   0
33      N09 Stroke large  0.59703600   0
34      N10 Stroke large  0.72751400   0
35      N17 Stroke large  0.63878400   0
36      N23 Stroke large  0.65749100   0
37      N24 Stroke large  0.60945900   0
38      N28 Stroke large          NA   0
39      N01 Stroke large -0.31610900   3
40      N07 Stroke large -0.33615700   3
41      N09 Stroke large -0.24906400   3
42      N10 Stroke large  0.33868700   3
43      N17 Stroke large -0.31357300   3
44      N23 Stroke large -0.13162800   3
45      N24 Stroke large -0.45343700   3
46      N28 Stroke large -0.18206700   3
47      N01 Stroke large -0.05309070   7
48      N07 Stroke large -0.83318300   7
49      N09 Stroke large -0.49667100   7
50      N10 Stroke large -0.48083200   7
51      N17 Stroke large -0.28447000   7
52      N23 Stroke large  0.01842660   7
53      N24 Stroke large -0.50464400   7
54      N28 Stroke large  0.16456100   7
55      N01 Stroke large  0.24652600  21
56      N07 Stroke large -0.31566500  21
57      N09 Stroke large  0.39618900  21
58      N10 Stroke large -0.30702200  21
59      N17 Stroke large -0.28860100  21
60      N23 Stroke large -0.23851000  21
61      N24 Stroke large -0.00913697  21
62      N28 Stroke large  0.43462600  21
63      N01 Stroke large -0.20660100  49
64      N07 Stroke large -0.13044900  49
65      N09 Stroke large  0.24625000  49
66      N10 Stroke large -0.28206200  49
67      N17 Stroke large  0.29186400  49
68      N23 Stroke large -0.14246600  49
69      N24 Stroke large -0.11297700  49
70      N28 Stroke large  0.32027300  49
71      N01 Stroke large -0.00106427  70
72      N07 Stroke large -0.17264000  70
73      N09 Stroke large  0.26417500  70
74      N10 Stroke large -0.11202200  70
75      N17 Stroke large  0.16687700  70
76      N23 Stroke large -0.24308300  70
77      N24 Stroke large  0.00322026  70
78      N28 Stroke large  0.34928100  70
79      C01      Control          NA   0
80      C02      Control          NA   0
81      C03      Control          NA   0
82      C04      Control          NA   0
83      C05      Control          NA   0
84      C06      Control          NA   0
85      C07      Control          NA   0
86      C09      Control          NA   0
87      C10      Control          NA   0
88      C32      Control          NA   0
89      C01      Control  0.32387500   3
90      C02      Control  0.48334200   3
91      C03      Control  0.70698800   3
92      C04      Control  0.00572262   3
93      C05      Control  0.40416000   3
94      C06      Control  0.36343800   3
95      C07      Control  0.05064140   3
96      C09      Control  0.84621500   3
97      C10      Control  0.80675300   3
98      C32      Control          NA   3
99      C01      Control  0.23174400   7
100     C02      Control  0.36959100   7
101     C03      Control  0.43762800   7
102     C04      Control  0.34187100   7
103     C05      Control  0.74288400   7
104     C06      Control  0.17692600   7
105     C07      Control  0.60067600   7
106     C09      Control  0.80314900   7
107     C10      Control  0.81695500   7
108     C32      Control  0.19029400   7
109     C01      Control  0.45062600  21
110     C02      Control  0.62884500  21
111     C03      Control  0.33693200  21
112     C04      Control  0.76098800  21
113     C05      Control  0.59837500  21
114     C06      Control  0.39328800  21
115     C07      Control  0.55099400  21
116     C09      Control  0.75411500  21
117     C10      Control  0.72495100  21
118     C32      Control  0.66503400  21
119     C01      Control  0.63903900  49
120     C02      Control          NA  49
121     C03      Control  0.59655200  49
122     C04      Control  0.42958700  49
123     C05      Control  0.68408700  49
124     C06      Control  0.45482700  49
125     C07      Control  0.37217700  49
126     C09      Control  0.75770400  49
127     C10      Control  0.62059200  49
128     C32      Control  0.68320900  49
129     C01      Control  0.66179300  70
130     C02      Control  0.34183000  70
131     C03      Control  0.58543900  70
132     C04      Control  0.62621700  70
133     C05      Control  0.40610400  70
134     C06      Control  0.32596100  70
135     C07      Control  0.14847100  70
136     C09      Control  0.79177000  70
137     C10      Control  0.71970900  70
138     C32      Control  0.56702700  70

This is our model:

model <- lme( na.action = na.omit, data = data, fixed = value ~ group *
time, random = ~1 | subject, correlation = corCAR1( form = ~time | subject )
)



anova( model )

            numDF denDF  F-value p-value
(Intercept)     1    87 59.08836  <.0001
group           2    20 34.50706  <.0001
time            1    87 19.45032  <.0001
group:time      2    87  4.53603  0.0134



intervals( model )

Approximate 95% confidence intervals

 Fixed effects:
                               lower          est.        upper
(Intercept)             0.3677066515  0.4905816494  0.613456647
groupStroke large      -0.9027833601 -0.7106686760 -0.518553992
groupStroke small      -0.6705657199 -0.4490365094 -0.227507299
time                   -0.0013629996  0.0009963115  0.003355623
groupStroke large:time -0.0003754957  0.0031296769  0.006634850
groupStroke small:time  0.0019261801  0.0059657552  0.010005330
attr(,"label")
[1] "Fixed effects:"

 Random Effects:
  Level: subject
                     lower      est.     upper
sd((Intercept)) 0.07377088 0.1227132 0.2041257

 Correlation structure:
        lower      est.     upper
Phi 0.2035765 0.5971507 0.8957905
attr(,"label")
[1] "Correlation structure:"

 Within-group standard error:
    lower      est.     upper
0.1779472 0.2071400 0.2411220

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