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please Help me on a repeated measures anova

6 messages · Dennis Murphy, soileil, David Winsemius

#
I currently work on a draft of an aquatic bioassessment. The conditions
tested are the following: ER river water T dechlorinated water control 0.5 +
0.5mg / L of malate T + 1 dechlorinated water control + 1g / L of malate T
ED dechlorinated water control SED + ER + river water sediment SED ED +
sediment + water dechlorinated. It is the result of AChE in muscle (fillet
of fish). The production of acetylcholine is followed with a
spectrophotometer every 15 seconds for two minutes. The results are
presented in the following table:


traitement t15 t30 t45 t60 t75 t90 t105 t120
ER 0.100 0.110 0.123 0.135 0.147 0.159 0.171 0.182
ER 0.112 0.134 0.153 0.174 0.192 0.208 0.226 0.251
T+0.5 0.078 0.082 0.088 0.094 0.101 0.108 0.113 0.120
t+0.5 0.053 0.100 0.109 0.120 0.127 0.136 0.145 0.154
TED 0.107 0.126 0.141 0.161 0.172 0.184 0.200 0.213
TED 0.117 0.135 0.153 0.169 0.183 0.201 0.218 0.229
TED 0.124 0.145 0.163 0.187 0.208 0.227 0.244 0.259
T+1 0.109 0.119 0.134 0.148 0.163 0.174 0.187 0.202
T+1 0.118 0.134 0.153 0.170 0.184 0.197 0.214 0.228
SED+ER 0.158 0.175 0.194 0.208 0.226 0.240 0.259 0.268
SED+ED 0.119 0.140 0.157 0.174 0.192 0.208 0.225 0.240
SED+ED 0.101 0.113 0.180 0.140 0.154 0.166 0.179 0.190
SED+ED 0.129 0.135 0.140 0.146 0.153 0.159 0.165 0.172


The statistical test is considered a repeated measures anova but I do not
know how to do it in R. I watched the forums and I downloaded the R package
'nlme' by which I should be able to use the function 'lm'. But the problem
is that I can not encode this function. Could you help me?
8 days later
#
In fact, the imbalance of repetitions is a time effect. Indeed, some measures
have been carried out in the morning and another in the afternoon. And we
could show this difference with a Friedman. So the question I ask myself
after what I had just read is that there is no difference? Increasing the
enzyme concentration was correlated with time?
#
So far I've done this:
Temps.s. Modalite  AchE
1         15       ER   0,1
2         15       ER 0,112
3         15    T+0,5 0,078
4         15    T+0,5 0,053
5         15      TED 0,107
6         15      TED 0,117
7         15      TED 0,124
8         15      T+1 0,109
9         15      T+1 0,118
10        15   SED+ER 0,158
11        15   SER+ED 0,119
12        15   SED+ED 0,101
13        15   SED+ED 0,129
14        30       ER  0,11
15        30       ER 0,134
16        30    T+0,5 0,082
17        30    T+0,5   0,1
18        30      TED 0,126
19        30      TED 0,135
20        30      TED 0,145
21        30      T+1 0,119
22        30      T+1 0,134
23        30   SED+ER 0,175
24        30   SER+ED  0,14
25        30   SED+ED 0,113
26        30   SED+ED 0,135
27        30       ER 0,123
28        30       ER 0,153
29        30    T+0,5 0,088
30        30    T+0,5 0,109
31        30      TED 0,141
32        30      TED 0,153
33        30      TED 0,163
34        30      T+1 0,134
35        30      T+1 0,153
36        30   SED+ER 0,194
37        30   SER+ED 0,157
38        30   SED+ED  0,18
39        30   SED+ED  0,14
40        60       ER 0,135
41        60       ER 0,174
42        60    T+0,5 0,094
43        60    T+0,5  0,12
44        60      TED 0,161
45        60      TED 0,169
46        60      TED 0,187
47        60      T+1 0,148
48        60      T+1  0,17
49        60   SED+ER 0,208
50        60   SER+ED 0,174
51        60   SED+ED  0,14
52        60   SED+ED 0,146
53        75       ER 0,147
54        75       ER 0,192
55        75    T+0,5 0,101
56        75    T+0,5 0,127
57        75      TED 0,172
58        75      TED 0,183
59        75      TED 0,208
60        75      T+1 0,163
61        75      T+1 0,184
62        75   SED+ER 0,226
63        75   SER+ED 0,192
64        75   SED+ED 0,154
65        75   SED+ED 0,153
66        90       ER 0,159
67        90       ER 0,208
68        90    T+0,5 0,108
69        90    T+0,5 0,136
70        90      TED 0,184
71        90      TED 0,201
72        90      TED 0,227
73        90      T+1 0,174
74        90      T+1 0,197
75        90   SED+ER  0,24
76        90   SER+ED 0,208
77        90   SED+ED 0,166
78        90   SED+ED 0,159
79       105       ER 0,171
80       105       ER 0,226
81       105    T+0,5 0,113
82       105    T+0,5 0,145
83       105      TED   0,2
84       105      TED 0,218
85       105      TED 0,244
86       105      T+1 0,187
87       105      T+1 0,214
88       105   SED+ER 0,259
89       105   SER+ED 0,225
90       105   SED+ED 0,179
91       105   SED+ED 0,165
92       120       ER 0,182
93       120       ER 0,251
94       120    T+0,5  0,12
95       120    T+0,5 0,154
96       120      TED 0,213
97       120      TED 0,229
98       120      TED 0,259
99       120      T+1 0,202
100      120      T+1 0,228
101      120   SED+ER 0,268
102      120   SER+ED  0,24
103      120   SED+ED  0,19
104      120   SED+ED 0,172
Erreur dans storage.mode(y) <- "double" : 
  la modification du mode de stockage d'un objet 'factor' n'est pas
autoris?e
De plus : Messages d'avis :
1: In model.response(mf, "numeric") :
  l'utilisation de type="numeric" avec une r?ponse de type facteur sera
ignor?e
2: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
  les arguments surnum?raires random sont ignor?s.

What is my mistake?
#
On Dec 30, 2010, at 5:38 AM, soileil wrote:

            
snipped data
Even without an English translation, it seems very likely that the  
AchE variable is not of numeric class,  but rather a factor. You may  
want to redo your data input step with a setting for the decimal  
separator set properly for the conventions of your locale settings.  
See help(read.table)

You may also want to look at the settings for locale if you will  
typically be using "," as a decimal separator.

?options
?locales
#
On Dec 30, 2010, at 10:11 AM, David Winsemius wrote:

            
And the other _big_  problem that I did not notice at first is that  
you are overwriting your data with the model output. This isn't  
exactly the problem addressed by fortune("dog") but an even more  
severe case of identity conflation. This is even a further example of  
why it is a bad idea to use the attach function.
David Winsemius, MD
West Hartford, CT