Selecting a test to determine when to end an experiment?We have an experiment testing a population's response to a chemical with three sampling points in time. The measurements at these time points are the dosage with a significant effect on the test population.
I want to know if the measurements at the first and last time points (middle time point too) are normally equal or different. It would save money to end the experiment at sampling point 1 if the results are typically representative of the later time points (2 or 3). I have a large data set of test of 100 chemicals I would like to do this analysis on
I am at a loss for structuring this and I have spend hours playing around with different approaches. Because the dosage values with an effect are not random, they depend on the range of dosage values selected in the experiment, and the effect magnitude is a function of the the organism's response to that specific chemical, I would think that a repeated measures anova is not correct. Also the data is non-normal even after log transformation. I just care if the value is the same or different during the duration of the experiment
Maybe a chi square would be the correct here with discrete value "is the same or not"? Maybe an agreement statistic, but that would only work with two time cases. I just care if the value is the same or different across the three time points
This is the current structure
Dosage with an effect
Day 10 Day 20 Day 30
Chem x .5 .5 .3
Chem y 2 1 .2
Chem z 1 .15 .15
AnalyticsRe: Selecting a test to determine when to end an experiment?Set the analysis up as a two-way ANOVA, with Chem and Day as fixed effects, with an interaction. So three columns: Chem, Day, and Y. Then select Analyze > Fit Model. Select Y and click Y. Select Chem and Day and click Macros > Factorial. Click Run.
Evaluate the Effect Tests for the Day and Chem*Day terms.
Re: Selecting a test to determine when to end an experiment?I get overfitting when I try to do it that way. A few of the tests are missing the second time point and many of the values are repeats if the measurement didn't change across sampling points. I am wondering if that is what lead to this outcome. Very odd that I dont have any DF for my day variable. Any suggestions? Thank you!
Re: Selecting a test to determine when to end an experiment?I am sorry. The two-way ANOVA model not be the most efficient give the limited data that you have. There is no replication, so my first approach results in a saturated model.
It is reasonable to instead treat Day as a continuous linear fixed effect Be sure that the modeling type for Day is Continuous, not Nominal or Ordinal. Then follow the same steps as I first described. You should get a result like this:
These results suggest that there is a difference in the response across Chem levels, but the Day makes not significant difference.
Re: Selecting a test to determine when to end an experiment?Even when changing day to continuous I get overfitting:
Interestingly if I model Pesticide as a nested random effect under the type of pesticide (nominal classification) and structure the comparison like a repeated measures mixed model I get meaningful results:
I am conflicted thought, because part of me thinks that pesticide shouldn't be random in this instance. But maybe for the question I am interested in it should be.
Re: Selecting a test to determine when to end an experiment?
I guess a nested two way anova will work for my needs. But I wonder why it was overfitting with the non nested?? Let me know if you have thoughts
