Dear all,
A researcher came with this design of data and asked me which statistical test will be the most appropriate to see if the difference after treat ment between cells1 and cells2 is significant...
I have now to mention that I am not a statistician. After having a look, it seems that Two-way repeated-measures ANOVA would be the most appropriate test. Is it correct?
I set the model like this: Value ~ Cell * Treatment + Error(Experiment/Treatment)
and called
But I am absolutely not sure about my model and I do not understand the output...
Thanks in adavance,
s.
A researcher came with this design of data and asked me which statistical test will be the most appropriate to see if the difference after treat ment between cells1 and cells2 is significant...
Code:
>mydata Cell Experiment Treatment Value 1 Cell1 1 untreated 4.41 2 Cell1 1 treated 17.60 3 Cell1 2 untreated 4.10 4 Cell1 2 treated 11.50 5 Cell1 3 untreated 5.21 6 Cell1 3 treated 7.84 7 Cell2 1 untreated 4.67 8 Cell2 1 treated 5.55 9 Cell2 2 untreated 4.23 10 Cell2 2 treated 5.41 11 Cell2 3 untreated 5.61 12 Cell2 3 treated 7.69
I set the model like this: Value ~ Cell * Treatment + Error(Experiment/Treatment)
and called
Code:
aov.out <- aov(Value ~ Cell * Treatment + Error(Experiment/Treatment), data=mydata) > summary(aov.out) Error: Experiment Df Sum Sq Mean Sq F value Pr(>F) Residuals 2 7.056 3.528 Error: Experiment:Treatment Df Sum Sq Mean Sq F value Pr(>F) Treatment 1 62.38 62.38 11.28 0.0784 . Residuals 2 11.06 5.53 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Error: Within Df Sum Sq Mean Sq F value Pr(>F) Cell 1 25.52 25.521 2.882 0.165 Cell:Treatment 1 30.34 30.337 3.426 0.138 Residuals 4 35.42 8.855
But I am absolutely not sure about my model and I do not understand the output...
Thanks in adavance,
s.
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