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Thread: How to take into account different treatments, doses and starting health

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    Re: How to take into account different treatments, doses and starting health




    Quote Originally Posted by Rickyroughneck View Post
    12.8 is just the average value per datum. 15 drops counted per nematode + treatment combination, each one averaging 12.8 nematodes.
    I don't understand this. What are you measuring? 15 drops of what? Did you for each treatment combination take 15 drops and measured number of nematodes and checked how many of these were alive and how many dead?

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    Re: How to take into account different treatments, doses and starting health

    Quote Originally Posted by GretaGarbo View Post
    I don't understand this. What are you measuring? 15 drops of what? Did you for each treatment combination take 15 drops and measured number of nematodes and checked how many of these were alive and how many dead?
    Yes exactly; the nematodes were in a liquid medium from which they were counted in 20 microlitre drops. The total number of nematodes, as well as the number of moving nematodes were counted.

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    Re: How to take into account different treatments, doses and starting health

    Let's see now. The treatment combination were:

    3 doses,
    4 chemical.

    That makes a balanced factorial experimental design of 3*4 = 12 experimental conditions.
    In addition 1 control with zero dose and thus no chemical. That makes 12 +1 = 13 experimental conditions.

    You also had 3 species but they are not really treatments. (I don't know how to think about them but they will triple the number of nematodes.)

    If you had randomized then you would have taken an experimental unit and assigned it to one of the 13 treatments. (To randomize means to do a lottery for where it should go.)

    If you had picked one nematode individual and randomly assigned it to one of the 13 treatments and checked if it was dead or alive (a Bernoulli experiment) and continued like that until you had 15 nematods per treatments, then that would have been 13 binomial experiments and you could have evaluated it with logit (as hlsmith wrote above).

    But I don't think you did it that way. Maybe you had a large group of nematods in 13 test tubes. If you had randomized each test tube to one of the 13 treatments it would have been a randomized experiment. But then you would have got an extra random term.

    This is like if you exposes pupils to 3 doses of exercise. But if you are not choosing individuals to the training program, but you are choosing a school class randomly to each training program, then the experimental unit is not the individual but the school class. So instead of having say, 15 children times 3 classes = n = 45, you just have n=3 experimental units. If you randomize classes (test tubes) you will miss the extra variation that exists between the school classes (test tubes).

    Now I believe that the experiment can be evaluated as mixed model=multilevel model with dose and chemical as fixed explanatory factors and the test tube as a random effect.

    I hope the other ones will comment on this so that it will be a little bit more understandable.

    Edit: Ricky, please inform us about what is correct and what is not correct of what I said above.

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    Rickyroughneck (08-20-2017)

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    Re: How to take into account different treatments, doses and starting health

    Thanks for the reply, I have been learning various things about mixed models in SPSS. Still very confusing to understand all the different options but it feels like things are starting to come together!

    You are correct in that there were separate tubes for the different treatments, in fact there were three biological replicates per treatment (one per five drops) for a total of 39 tubes per nematode species. I have included them as an extra variable (thankfully I inputted the data chronologically!)

    The nematodes were taken from the same source though so there theoretically shouldn't be any difference (other than the chemical) between the tubes. Would tube still count as a random effect?

    I have run a mixed model and included dose as a nested effect within chemical, although I am not entirely sure about whether the single "dose(chemical)" term is sufficient for the model. I have also included tube number as a random effect. I am not sure at this stage if I have missed anything from the statistical test, would there be critical parameters or functions that I have missed?

    The interactions in the output are quite confusing. There are different significance values for all of the parameters, but I am not sure what interactions they are referring to. Ideally I would be finding how the chemicals compare against each other and the control.

    The fixed effects output is below:

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    Re: How to take into account different treatments, doses and starting health

    Sorry for the delay releasing your posts - they were caught in the spam filter. I've deleted the two first ones and kept the last, since it looks like you tried three times to post without success. Sorry about that - the filter sometimes flags posts from new members that include attachments.
    Matt aka CB | twitter.com/matthewmatix

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    Re: How to take into account different treatments, doses and starting health


    In addition to my previous post, is it possible to do post-hoc analysis with mixed models? Ideally I would have some kind of "Tukey" test to compare the effectiveness of the chemicals against each other. What would be perfect would be to be able to run a combined analysis of all three nematode species at once (with nematode, chemical and dose as factors, dose nested within chemical).

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