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?
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?
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?
Erreur dans storage.mode(y) <- "double" :
la modification du mode de stockage
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
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?
--
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Erreur dans storage.mode(y) <- "double" :
la modification du mode de stockage
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)
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.
You may also want to look at the settings for locale if you will
typically be using "," as a decimal separator.
?options
?locales
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?
--
View this message in context: http://r.789695.n4.nabble.com/please-Help-me-on-a-repeated-measures-anova-tp3159868p3168134.html
Sent from the R help mailing list archive at Nabble.com.