[R] question

Tue Jan 31 16:46:36 CET 2023

"The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data."

John Tukey

Cheers,
Bert

On Tue, Jan 31, 2023 at 7:44 AM Carolyn J Miller via R-help <
r-help using r-project.org> wrote:

> Hi Boris,
>
> It's hair cortisol so it shouldn't have an effect. My study species are
> ungulates, which retain their coat through the winter into the spring
> shedding out around April/May so in theory these two sampling periods
> should provide the same results as hair cort provides an average of
> accumulated cort levels released into the hair over that growth period
> until they shed out. Of course the individuals that had hair collected in
> March instead of December have had longer to incorporate more cort levels
> into the hair collected in comparison to their conspecifics captured in
> December.
>
> I had a repeated measures approach to this previously but due to missing
> data from uneven captures the model gets angry since there's only 2 levels
> of replication and many are not repeated at all. We're considering dividing
> up the dataset by season to eliminate the need for repeated measures. I've
> had it suggested that we should use the single measure of cort (which is
> what most individuals have) in both rows (March and December) based on this
> logic, and then just run the models as separate seasons.
>
> I ran the t-test between the march and december cort samples and they are
> not representing the same information.
>
> The joys of data analysis!
>
> Thanks for your feedback,
>
> Carolyn J. Miller
> M.S. Student, Ecology
> SUNY-ESF, Environmental Biology
>
>
> ________________________________
> From: Boris Steipe <boris.steipe using utoronto.ca>
> Sent: Tuesday, January 31, 2023 10:16 AM
> To: Carolyn J Miller <cjmill04 using syr.edu>
> Cc: r-help using r-project.org <r-help using r-project.org>
> Subject: Re: [R] question
>
> Perhaps, rather than looking to compress your observations into a single
> number, you could simply visualize what you observed: use a boxplot to show
> the March and December observations, and overlay the three animals that
> were recaptured as individual points, connected with a line.
>
> Feel free to ask again if you are not sure how to do that.
>
> Cheers,
> Boris
>
>
> PS. Lets hope that the capture did not stress them to the degree that
> their cortisol is elevated at recapture :-)
>
>
>
>
> > On 2023-01-31, at 09:52, Carolyn J Miller via R-help <
> r-help using r-project.org> wrote:
> >
> > Thank you!
> >
> > Carolyn J. Miller
> > M.S. Student, Ecology
> > SUNY-ESF, Environmental Biology
> >
> >
> > ________________________________
> > From: Ebert,Timothy Aaron <tebert using ufl.edu>
> > Sent: Tuesday, January 31, 2023 9:50 AM
> > To: Carolyn J Miller <cjmill04 using syr.edu>; PIKAL Petr <
> petr.pikal using precheza.cz>; r-help using r-project.org <r-help using r-project.org>
> > Subject: RE: question
> >
> >
> > As indicated here:
> https://www.geeksforgeeks.org/compute-the-correlation-coefficient-value-between-two-vectors-in-r-programming-cor-function/
> >
> > The cor() function needs two vectors. The only way that works is if you
> are looking at the correlation between �Month� and �Cort.�
> >
> > If you interested in the correlation between  Cort measured in month 3
> versus month 12 then you are not getting the right answer.
> >
> >
> >
> > Animal ID is not relevant in this analysis (as presented).
> >
> > The animals that have been measured twice would be a repeated measures
> analysis (by default) unless there is some reason to suspect that the six
> month lag is too long for an outcome in month 3 to influence the outcome in
> month 12. The remaining animals are an experimental design for avoiding a
> repeated measures analysis. This would be something like a t-test to
> determine if the animals in Month 3 are different than Month 12.
> >
> >
> >
> > Tim
> >
> >
> >
> > From: Carolyn J Miller <cjmill04 using syr.edu>
> > Sent: Tuesday, January 31, 2023 9:30 AM
> > To: PIKAL Petr <petr.pikal using precheza.cz>; r-help using r-project.org;
> Ebert,Timothy Aaron <tebert using ufl.edu>
> > Subject: Re: question
> >
> >
> >
> > [External Email]
> >
> > Hi Timothy,
> >
> >
> >
> > Here's some example data that might help to demonstrate how the data
> currently looks.
> >
> >
> >
> > AnimalID
> >
> > Month
> >
> > Cort
> >
> > 1
> >
> > 12
> >
> > 0.00591
> >
> > 1
> >
> > 3
> >
> > 0.00583
> >
> > 2
> >
> > 3
> >
> > 0.005722
> >
> > 3
> >
> > 3
> >
> > 0.005838
> >
> > 4
> >
> > 3
> >
> > 0.005873
> >
> > 4
> >
> > 12
> >
> > 0.0059
> >
> > 5
> >
> > 3
> >
> > 0.005724
> >
> > 6
> >
> > 12
> >
> > 0.005924
> >
> > 7
> >
> > 12
> >
> > 0.005758
> >
> > 8
> >
> > 12
> >
> > 0.005901
> >
> > 9
> >
> > 12
> >
> > 0.005894
> >
> > 10
> >
> > 3
> >
> > 0.005731
> >
> > 11
> >
> > 3
> >
> > 0.005951
> >
> >
> >
> > So Animal ID represents individual, 3 or 12 for month represents either
> a March capture event or a December capture event and then the
> corresponding cort value (which I used a random number generator to create
> these values above). Petr, I was afraid of that response, that by using
> cor() I'm fundamentally just testing the correlation for the 3 individuals
> that have both March and December samples.
> >
> >
> >
> > If you guys have other thoughts I'd appreciate any suggestions.
> >
> >
> >
> > Thanks for your help and clarifying that for me.
> >
> >
> >
> > Carolyn J. Miller
> >
> > M.S. Student, Ecology
> >
> > SUNY-ESF, Environmental Biology
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > ________________________________
> >
> > From: PIKAL Petr
> > Sent: Tuesday, January 31, 2023 2:36 AM
> > To: Carolyn J Miller; r-help using r-project.org<mailto:r-help using r-project.org>
> > Subject: RE: question
> >
> >
> >
> > Hallo Carolyn
> >
> > From what you describe you cannot calculate correlations.
> >
> > You stated that you have two sets of data, one for December and one for
> > March and that rows in one set is not related to the rows in another set
> and
> > even persons tested in both months do not have their values on the same
> row.
> > In that case cor is not appropriate. You should first adjust your data so
> > that results of those 3 persons are on the same row but even after that
> only
> > those 3 values could be evaluated by "cor".
> >
> > From what you wrote I think that t.test or similar beast is the way you
> > should take.
> >
> > But without same data sample I may be wrong.
> >
> > Cheers
> > Petr
> >
> >> -----Original Message-----
> >> From: R-help <r-help-bounces using r-project.org<mailto:
> r-help-bounces using r-project.org>> On Behalf Of Carolyn J Miller
> > via
> >> R-help
> >> Sent: Monday, January 30, 2023 7:16 PM
> >> To: r-help using r-project.org<mailto:r-help using r-project.org>
> >> Subject: [R] question
> >>
> >> Hi guys,
> >>
> >> I am using the cor() function to see if there are correlations between
> > March
> >> cortisol levels and December cortisol levels and I'm trying to figure
> out
> > if the
> >> function is doing what I want it to do.
> >>
> >> Each sample has it's own separate row in the CSV file that I'm working
> out
> > of.
> >> March Cort and December Cort are different columns and they come from
> >> separate samples, therefore their values would not be on the same row.
> > There
> >> are only 3 individuals that have both December cort values and March
> > cortisol
> >> values but they still have different sample ID values (from different
> > seasons) so
> >> they are also not on the same row.
> >>
> >> I ran the function twice: once as cor(cortphcor, use = "complete.obs")
> > first
> >>
> >> and then cor(cortphcor, use = "pairwise.complete.obs", method =
> > "pearson").
> >>
> >> I received the same output both times. I guess what I'm asking is, is
> the
> > output
> >> simply the correlation just for those 3 samples or is the second
> pairwise.
> >> complete.obs version giving me the correlation for all of the cort
> samples
> > for
> >> March against all of the samples for December despite not being on the
> > same
> >> row? I'm trying to figure out how many sample values are contributing to
> > the
> >> correlation results I'm getting.
> >>
> >> Thanks,
> >>
> >> Carolyn
> >>
> >>
> >>       [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
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> >
> >        [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
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> > and provide commented, minimal, self-contained, reproducible code.
>
>
> --
> Boris Steipe MD, PhD
>
> Professor em.
> Department of Biochemistry
> Temerty Faculty of Medicine
> University of Toronto
>
>
>
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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