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Thread: [R] Between subjects repeated measures ANOVA help. Level: Novice.

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.




    Dear Greta and Victorxstc, I am currently away on a business trip and will be back on Monday. I hope that we can continue this discussion when I arrive home, thank you once again.

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Quote Originally Posted by victorxstc View Post
    Greta, I think pickle assumes (as he/she already confirmed) that the previous deformations are totally elastic, meaning that at these loads, absolutely no permanent deformations remain (or if there remains some ultra microscopical deformations, we can ignore them and consider them non-existent). Pickle, I personally think your design is limited (like many other studies on expensive materials) but not invalid. You have still pairs of Force-Brand which can be used to predict the extent of deformation. Although as Greta said, it was better to exert each force-brand on a new piece of implant, it is not practically possible sometimes. So I think your design can be accepted.
    That is true. My study was funded from my own pocket so I could not have ideal conditions (even though I made an enormous effort to do everything by the book). Thank you for accepting my design.

    Now I think your question is that "are your results valid"? I haven't read them yet, but I think why not? If you have used the correct test, and the assumptions of the test are met, why not? OK exerting 11 x 3 forces at a single point of each implant might be somehow limiting. If possible, I would rotate the implant at each trial, so that each new force would be exerted to a new point (of course if the implant design was symmetric, which I think it was). But even in your current design, as far as those forces did not bend the implant, or did not change the shape of the loading area (I mean the geometry of the small area at which the force is applied), it could be OK to load the same point frequently. I am not concerned with the former as you already told us that forces up to 120 N do not bend the implant permanently (to the plastic point) (even at microscopical level). But I am not sure whether titanium alloy is malleable or not under the forces up to 120 N.
    Implants look like cylinders and they were rotated to a certain extent at each trial - only their position remained the same.

    You can use a repeated-measures ANOVA and its posthoc, or at least a paired t-test for this purpose. Put the results of all the implants in rows and differentiate them according to the number of the force application rounds (a table of 5 x 11 = 55 rows and 3 columns). Then using a t-test, check if there is a significant trend in the values in the first round compared to the second, and between the second and third rounds. If there were no significant changes between the three rounds of force application, it means that OK the error introduced into your design by ultra-microscopic deformations at each trial is not affecting your results (of course if your test power was sufficient [which I guess it would be, given the good sample size of yours]).
    The changes were within the method sensitivity error, so I believe that I could use the average values.

    However, you could still tend to use them and take the averages of the three trials of each Force-Brand. Using the second and third trials would of course introduce some measuring bias into your results (if there was a significant decrease in your deformations in the second and third trials). In particular, your Mean values would become affected (the mean would reduce or increase a little bit of course). But the correlations between the independent and dependent variables might still be valid. Although I do not recommend this option (even though I think the changes in the mean value would be really small, if detectable).
    My supervisor advised me to use the average values the other day. If I use the average values, then I suppose that Greta's advice on performing ANOVA remains valid and that I can use the ANOVA tables obtained using Greta's code?


    I suggest you to report as well the results of the statistical assessment of the validity of the second and third trials in your thesis (and later, article) [and also here, if you wished].
    I most certainly will inform you about everything that I am doing with this study. Thank you.

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    Talking Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Dentistometrics?
    Fine by me

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Dear Greta and Victorxstc,

    could you help me with residuals? How do I analyse them in R?
    Sorry for asking this many questions, but I am confused with those 4 graphs that I get (Residuals vs Fitted, Scale-Location, Normal Q-Q and Residuals vs Factor Levels).

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Hi pickle, hope your vacation went well!

    Implants look like cylinders and they were rotated to a certain extent at each trial - only their position remained the same.
    Ok then I think no other problems remain! No worries for affecting the loading point etc. by exerting the force at the same point.

    The changes were within the method sensitivity error, so I believe that I could use the average values.
    Nice!

    My supervisor advised me to use the average values the other day. If I use the average values, then I suppose that Greta's advice on performing ANOVA remains valid and that I can use the ANOVA tables obtained using Greta's code?
    Indeed. You can use an ANOVA as long as its assumptions are met. Many reports use average values between trials. As a matter of fact, the number of reports which use averages surpass by far those which use each data piece independently. So the method advised by your professor is totally fine, although the other method could be better.

    I most certainly will inform you about everything that I am doing with this study. Thank you. Reply
    Thanks.

    could you help me with residuals? How do I analyse them in R?
    Sorry for asking this many questions, but I am confused with those 4 graphs that I get (Residuals vs Fitted, Scale-Location, Normal Q-Q and Residuals vs Factor Levels).
    You are so welcome. In your case, the normal distribution of residuals guarantees that you can use an ANOVA. In brief, a Q-Q plot with residuals aligned on the oblique straight line shows that your residuals are normally distributed. Although its interpretation is subjective, a straight alignment of residuals is usually obviously distinguishable. But I suggest you attaching your graphs here so that Greta can help you (she is not good with subjective tasks!).

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    pickle (02-28-2013)

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    Red face Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Thank you for so much help.

    This is one of my residuals analyses. The other two (I did 3 ANOVAs altogether, comparing brands among narrow diameter implants, comparing brands among wide diameter implants and comparing narrow and wide diameter implants) look almost the same.
    Attached Images  

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    You are so welcome

    Your graphs show that the residuals are well-behaved, their variance is constant, only a few outliers exist (which I think should not be removed from the model), their distribution is quite normal, and the leverage is similar for the observations.

    So I guess you have a good sample to run the ANOVA!

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    pickle (03-01-2013)

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    This forum is amazing.

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Hmm, well, eh,...
    Although the graphs like fine, the above code that I gave is still not valid. That code was based on the assumption that there was 11 units per brand but there was just one (1).

    @trinker and others:

    When I asked above about where trinker saw a “repeated measurement layout” it was a real question about his interpretation of the design (and not a “confrontational” question). I thought that maybe he saw through what was going on and saw a repeated measures design or a random effect design.

    Trinker suggested the “ez” R package and the book by Field. I or our library does not have access to that book. Does trinker or anybody else have any suggestions about documentation and examples of “ez” package?

    I made an interpretation of the design that was a possible one, but it turned out to be an incorrect interpretation. Now it really looks like a repeated measures layout.

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.

    Any help on what I should do now?

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    Re: [R] Between subjects repeated measures ANOVA help. Level: Novice.


    @trinker and others:

    When I asked above about where trinker saw a “repeated measurement layout” it was a real question about his interpretation of the design (and not a “confrontational” question). I thought that maybe he saw through what was going on and saw a repeated measures design or a random effect design.

    Trinker suggested the “ez” R package and the book by Field. I or our library does not have access to that book. Does trinker or anybody else have any suggestions about documentation and examples of “ez” package?
    Whoah forgot about this thread.

    I only jumped to conclusions based on the post's title. So early on it didn't look like a repeated measures. There's a lot in this thread now for me to go back through. What indicates to you Greta that it is a repeated measures?

    Sorry on the Andy Field book. I actually just purchased it as it's a good one for me to have in the arsenal. I looked around a bit for stuff on the ez package but on the cran manual's were evident to me. The examples in there aren't too bad but may be for a beginner. There's a lot of other approaches in R but this has been pretty east for me to teach to classmates just starting out over lme4 (not that I even grasp that package even 12%). I think nmle is also pretty straight forward and there are googlable texts to help with these ones.
    "If you torture the data long enough it will eventually confess."
    -Ronald Harry Coase -

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