[R-sig-ME] Single DV with multiple measures for time-varying IV?
Pero, Ellen
ellen@pero @ending from umconnect@umt@edu
Wed Nov 21 16:28:58 CET 2018
Thank you Bill and Thierry.
I don't yet have data in hand (cortisol samples await assay). However, this is what they will look like:
cortisol
---------------------------------
ID DV Month 1 Month 2 ... Month 8 dam age, sire age, calf birthdate
1 ....
2 ....
.. ....
60 ....
While I can simulate more data, my primary question is theoretical:
Is it acceptable practice to share a single dependent response (DV: here calf mass (kg)) amongst multiple time-varying nested independent predictors (here, monthly cortisol) as long as I place a random effect to signify the individual I am nesting on (ID).
ID DV cortisol, time, dam age, sire age, calf birthdate
1 17 35 Month 1 4 3 140
1 17 42 Month 2 4 3 140
........................................................
1 17 58 Month 8 4 3 140
2 19 30 Month 1 3 5 150
2 19 33 Month 2 3 5 150
........................................................
2 19 42 Month 7 3 5 150
........................................................
60 14 51 Month 2 2 2 162
60 14 58 Month 3 2 2 162
........................................................
60 14 70 Month 8 2 2 162
>From my digging, I don't think it is good practice. So, for now, I am planning to average repeated cortisol samples within an individual to produce an 'early' and 'late' value, and include both as covariates within a glm.
I appreciate your support and encouragement!
El
Ellen Pero
PhD Student
Wildlife Biology Program
W.A. Franke College of Forestry and Conservation
University of Montana
32 Campus Drive, FOR 318
Missoula, MT 59812
________________________________
From: Bill Poling <Bill.Poling using zelis.com>
Sent: Monday, November 19, 2018 4:26 AM
To: Pero, Ellen
Cc: Thierry Onkelinx; r-sig-mixed-models using r-project.org; Bill Poling
Subject: RE: [R-sig-ME] Single DV with multiple measures for time-varying IV?
Hi Ellen.
If the data frame is not too terribly large, a dput() would be useful.
See ?dput()
Or a str() would help as well
See ?str()
However, as Thierry suggests a subset of your data would be most helpful.
I will be interested to follow this topic as I am teaching myself R and learning the various modeling methods and their purposes along the way.
I think you will gain considerable support from this list relevant to your topic.
Best regards.
WHP
From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> On Behalf Of Thierry Onkelinx via R-sig-mixed-models
Sent: Monday, November 19, 2018 4:01 AM
To: ellen.pero using umconnect.umt.edu
Cc: r-sig-mixed-models <r-sig-mixed-models using r-project.org>
Subject: Re: [R-sig-ME] Single DV with multiple measures for time-varying IV?
Dear Ellen,
An extract of your dataset or a small dummy dataset coverting the important
features of your data would make it much easier to answer your questions.
And please don't send HTML emails. Any HTML formating gets stripped which
can make your email very hard to read.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
mailto:thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
http://www.inbo.be
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than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
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.
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Op ma 12 nov. 2018 om 20:01 schreef Pero, Ellen <
mailto:ellen.pero using umconnect.umt.edu>:
> Hi all:
>
> I have an analytical dilemma wherein I have a single DV with multiple
> categorical and continuous IVs (one of which is a continuous IV that has
> multiple measurements across time). I'm not sure the best way to model for
> this - though it's clearly a hierarchical situation so I thought this might
> be a good venue to pose the question.
>
> Specifically, I have 60 pregnant elk from which I took monthly cortisol
> samples across gestation (some missing values, so 5-8 samples/female across
> gestation). I'm interested in how those stress measurements across
> gestation (along with a range of other IVs that don't vary with time, e.g.,
> dam age, sire age, calf birthdate) influence the birth mass of each
> female's calf.
>
> Any suggestions on analysis for situations where a single DV is predicted
> by longitudinal measures of time-varying IV (along with non-varying IVs)?
>
> I'm new to this list and will spend some time familiarizing myself with it
> - but was eager to get my question out. Apologies if this isn't the right
> venue for my non-development related question. Please disregard if
> appropriate.
>
> I appreciate any thoughts/advice/suggestions!
> El
>
>
>
> Ellen Pero
> PhD Student
> Wildlife Biology Program
> W.A. Franke College of Forestry and Conservation
> University of Montana
> 32 Campus Drive, FOR 318
> Missoula, MT 59812
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> mailto:R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
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