On 23/10/2014, at 18:17 PM, Gavin Simpson wrote:
On 22 October 2014 17:24, Chris Howden ch...@trickysolutions.com.au wrote:
A good place to start is by looking at your residuals to determine if
the normality assumptions are being met, if not then some form of glm
that correctly models the
I think there are actually 4 data points per level of some factor (after
seeing some of the other no-threaded emails - why can't people use emails
that preserve threads?**); but yes, either way this is a small data set and
trying to decide if residuals are normal or not is going to be nigh on
With such a small data set, why not simulate some data sets with reasonable
effect sizes and see how an analysis performs? Krzysztof
Dear Krzysztof,
It is good idea. Would you know some R functions thatis are well suited for
this kind of simulations
Why not take the opportunity of getting to know ABC some more? Rasmus
Bååth wrote a piece on Tiny Data and ABC which might suit your problem
very well.
http://www.r-bloggers.com/tiny-data-approximate-bayesian-computation-and-the-socks-of-karl-broman/
Cheers
/Lars
On 2014-10-22 08:19, V.
A good place to start is by looking at your residuals to determine if
the normality assumptions are being met, if not then some form of glm
that correctly models the residuals or a non parametric method should
be used.
But just as important though is considering how you intend to use your
data
Dear All,
Please do not take any offence, I would really like to be removed from this
mailing list, can someone let me know how this can be done.
Best Regards,
--
Nicholas Hamilton
School of Materials Science and Engineering
University of New South Wales (Australia)
--
www.ggtern.com
On 23
. 22443
ph. 410.610.1473
Date: Mon, 20 Oct 2014 10:53:41 +0200 (CEST)
From: V. Coudrain v_coudr...@voila.fr
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] Regression with few observations per factor level
Message-ID: 2127199056.738451413795221981.JavaMail.www@wwinf7128
Content-Type
Hi, I would like to test the impact of a treatment of some variable using
regression (e.g. lm(var ~ trt + cov)). However I only have four observations
per factor level. Is it still possible to apply a regression with such a small
sample size. I think that i should be difficult to correctly
-ecology@r-project.org
Objet : Re: [R-sig-eco] Regression with few observations per factor level
I think you can, but the confidence intervals will be rather large due to
number of samples.
Notice how standard errors change for sample size (per group) from 4 to 30.
pg - 4 # pg = per group
and the probability of getting a significant relation decreases. What
about the significant coefficients, are they reliable?
Message du 20/10/14 à 11h30
De : Roman Luštrik
A : V. Coudrain
Copie à : r-sig-ecology@r-project.org
Objet : Re: [R-sig-eco] Regression with few observations
, are they reliable?
Message du 20/10/14 à 11h30
De : Roman Luštrik
A : V. Coudrain
Copie à : r-sig-ecology@r-project.org
Objet : Re: [R-sig-eco] Regression with few observations per factor
level
I think you can, but the confidence intervals will be rather large due
to number
))
Elgin S. Perry, Ph.D.
Statistics Consultant
377 Resolutions Rd.
Colonial Beach, Va. 22443
ph. 410.610.1473
Date: Mon, 20 Oct 2014 10:53:41 +0200 (CEST)
From: V. Coudrain v_coudr...@voila.fr
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] Regression with few observations per factor level
to artificially makes
my data tell something if it cannot.
Message du 20/10/14 à 16h50
De : stephen sefick
A : Martin Weiser
Copie à : V. Coudrain , r-sig-ecology
Objet : Re: [R-sig-eco] Regression with few observations per factor level
You are more or less preforming an ANOVA/ANCOVA
[mailto:r-sig-ecology-boun...@r-project.org] On Behalf Of V. Coudrain
Sent: Monday, October 20, 2014 8:54 AM
To: ElginPerry
Cc: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] Regression with few observations per factor level
Thank you for this helpful thought. So if I get it correctly
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