Hi,
Urgent help- I have not been using R and statistics in my research for a
long time, but still remember some concept. I would like to have a sample
code for Manova analysis of Split-plot experiment. Could someone please post
a sample code and a short input sample as well?
Thank you so much!
Hi, Please suggest a method to answer below questions:
Factory_ID Factory_Location Factory_Size Total_Sample
Good_Sample Fair_Sample Bad_Sample
---
it the data well. The nice thing
> about it, is you can include a lot of predictions (e.g., that there
> will be more good samples than bad samples and that big factories will
> be better than small factories and that City A will be better than
> City B) all in one test.
>
> HTH,
&g
t; r.score <- t.score/sqrt((t.score^2)+df)
> value <- list(t.score, p.score, r.score, s2.pooled, df)
> names(value) <- c("t.contrast", "p.value", "r.contrast",
> "pooled.variance", "df")
> return(value)}
>
it is at
> least designed to handle different levels. I only have a rudimentary
> knowledge of multi-level models or logistic regression so I cannot
> offer much advice.
>
> Best of luck,
>
> Joshua
> \
>
--
Xiang Gao, Ph.D.
Department of Biology
University of North Texas
Dear R-helper,
Please suggest some methods for my question below.
We measured the amount of protein A in patient blood in pre-treatment and
post-treatment condition from 32 patients.
Pre-treatment Post-treatment
Pat1 25
Hi,
The permutation test for two samples in R is function perm.test(). I could
not figure out what is the statistics it estimate and how many permutation
it did in default?
Thanks,
[[alternative HTML version deleted]]
__
R-help@r-project.org m
om: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> > project.org] On Behalf Of Xiang Gao
> > Sent: Thursday, April 22, 2010 1:43 PM
> > To: r-help@r-project.org
> > Subject: [R] What is the test statistics in perm.test
> >
> > Hi,
> >
> > The
I have a question about the D'Agostino skewness test and the Anscombe-Glynn
kurtosis test.
agostino.test(x, alternative = c("two.sided", "less", "greater"))
anscombe.test(x, alternative = c("two.sided", "less", "greater"))
The option "alternative" in those two functions seems to be the null
hyp
a = PCBdata))
numDF denDF F-value p-value
(Intercept) 112 1841.7845 <.0001
Area 1 44.9846 0.0894
--
Xiang Gao, Ph.D.
Department of Biology
University of North Texas
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