I have trouble knowing the right statistical test that i need to use for my data.
I have a group of animals subjected to a task, where each animal is exposed to three or four conditions. The data does not follow a gaussian distribution, so i know that I have to use a non-parametric repeated measure test, that is Friedman test and Dunn's to compare between conditions. Then, i have independent groups of animals tested in the same task. To avoid groups variability I normalized the conditions, setting the control condition (first condition) from each group as 100%. Then, the problem is that if want to compare the change in just one condition between independent groups using the percentages obtained from the normalized data, can I use an one-way anova?
I hope that I can be clear this time.
ThanksI’m doing a behavioral task, in Advancewhich each animal is tested to find a piece of chocolate (I measure the latency to find it (latency of detection) in a 10 min trial). This is repeated four times, meaning 4 trials. For the control group, the animals were injected with saline between trial 1 and 2. Then the animals were injected with the X drug between trials 2 and 3, and finally were injected with the Y drug between trials 3 and 4.
Example:
Control group (n=10 rats)
Each rat:
Trial 1
ip injection (saline)
Trial 2
ip injection (X drug)
Trial 3
ip injection (Y drug)
Trial 4
End of the task.
I have two other groups that were injected with two different drugs (Z and A drugs) between trials 1 and 2, but the same X drug and Y drug given between trials 2 and 3, and 3 and 4.
Example:
Experimental groups (n=10 rats)
Each rat:
Trial 1
ip injection (Z or A drug)
Trial 2
ip injection (X drug)
Trial 3
ip injection (Y drug)
Trial 4
End of the task.
So the objective is to evaluate the effect of the X and Y drugs on the latency of detection in the control group, and later, if the Z or A drug change those effects observed in the control group.
To evaluate the effect of X and Y drugs on the control group I have to use an repeated measure test. But first, I did a normality test for the data obtained in the control group, and it showed me that the data does not follow a gaussian distribution. So, i figured that I have to use the Friedman test.
Then, to compare the change in the latency of detection induced by X and Y drugs between groups and evaluate if Z or A drugs modify it, I set the data obtained in the first trial for each group as 100% (this is to avoid group variability). Then I obtained a percentage of the change of the latency of detection for trials 2, 3 and 4 in control and experimental groups.
Example: Control group
Trial 1 (latency 100%)
ip injection (saline)
Trial 2 (latency 99.5%) no change
ip injection (X drug)
Trial 3 (latency 75%)
ip injection (Y drug)
Trial 4 (latency 43%)
End of the task.
Example: Experimental group 1
Trial 1 (latency 100%)
ip injection (Z drug)
Trial 2 (latency 99.8%) no change
ip injection (X drug)
Trial 3 (latency 95%)
ip injection (Y drug)
Trial 4 (latency 80%)
End of the task.
Example: Experimental group 2
Trial 1 (latency 100%)
ip injection (A drug)
Trial 2 (latency 98.8%) no change
ip injection (X drug)
Trial 3 (latency 105%)
ip injection (Y drug)
Trial 4 (latency 60%)
End of the task.
Therefore, in control group the X drug reduce the latency of detection to a 75% but the injection of Z drug modify it to a 95% or 105% if it used the A drug. At this point, i want to know if the effect of the X drug in control group is statistically different from the effect of the X drug in the experimental groups. For that case, I don’t know what statistical test suits my data.
Sorry for my lack of clarity. Thank very much for your help.
