is not required to do the sort.
Terry Therneau's kinship package does that ordering, but doesn't include
output routines for the Linkage format.
David Duffy.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
On Fri, 29 Jun 2007, Peter Dalgaard wrote:
David Duffy wrote:
Waverley [EMAIL PROTECTED] asked:
Dear Colleagues,
I am looking for a package or previous implemented R to subgroup and
exaustively divide a vector of squence into 2 groups.
--
Waverley @ Palo Alto
Google [R
or so.
David Duffy.
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG
that you could expand. You could
even partition out the studies using the party package (I believe it
does an ordinal logistic).
David Duffy.
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
),
filter=refsnp,
values=(refsnp=c(rs17166282,rs3897937)), mart=ensnp)
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research
useful (snps.by.name, snps.by.region, annotate.snps, maf: they
probably need to be updated before I show them off ;)).
David Duffy
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit
an ordered logistic in lrm() and using those estimates
as starting values (if it runs OK).
David Duffy.
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If they are structural zeros, I believe you want:
glm(COUNT ~ CONCERNS + AGE + GENDER, data=health, subset=(WEIGHTS0),
family=poisson)
David Duffy.
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
likelihood based
CI
using the Gibbs Chi-square (LRTS), but IIRC originally used the Pearson
chi-square.
I don't think there are R implementations.
David Duffy.
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
for everyone. The many time series packages may
also be usable for this.
David Duffy.
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research
Edition) has a chapter on bivariate survival
analysis (with our example in it;)).
David Duffy.
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, 8] - txt[i]
}
res[,7] - paste(res[,7], res[,8], sep=; )
res - res[,-8]
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300
On Mon, 24 Jul 2006, David Duffy wrote:
From: Bob Green [EMAIL PROTECTED]
I am hoping for some assistance with formatting a large text file which
consists of a series of individual records. Each record includes specific
labels/field names (a sample of 1 record (one of the longest ones
as a conditional logistic regression (look at clogit). I don't
think the sib TDT is as efficient as an FBAT approach, which can be applied to
that type of data.
David Duffy.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax
)
names(res) - names(your.data)[-seq(1,pos.first.marker-1)]
for (i in seq(1, Nsnps)) {
res[i] - tdt(your.data[,i], your.data)$p.value[2]
}
David Duffy
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
, timevar=marker,
idvar=id,direction=wide)
names(ped) - gsub(genotype.,, names(ped))
rpos - match(snps$Name, names(ped))
ped - ped[,c(1, rpos[!is.na(rpos)])]
ped
}
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217
I have missed a very simple trick.
Maybe something like:
x - data.frame(i=sample(1:10),j=1:10)
x2 - x[order(x$i),]
x2$k - cumsum(x2$j)
#
# 4 bins (;))
#
x2$bins - cut(x2$k,quantile(x2$k), labels=F)
x2
David Duffy.
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R-help@stat.math.ethz.ch mailing
Let's assume I have a vector of integers :
myvector - c(1, 2, 3, 2, 1, 3, 5)
For this, I create a table with ;
mytable - table(myvector)
1 2 3 5
2 2 2 1
However, table() returns an array of integers, mytable[4] returns the
occurence number of the 5 item, which makes this table hard to
%*% solve(E-p)
N=size of group
p=number of variables
E=expected covariance matrix
O=observed covariance matrix
where in your example, E will be the observed covariance matrix for
the pooled groups. There are GLS etc alternatives - see eg Bollen's book on
SEM.
| David Duffy (MBBS PhD
of Leeds/UK
lmekin and coxme in Terry Therneau's kinship package may help.
David Duffy.
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algorithms.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v
-p1)*(1-p2))
}
Y - X
i1 - X==1
i0 - X==0
Y[i1] - rbinom(sum(i1),1, p2 + covar/p1)
Y[i0] - rbinom(sum(i0),1, p2 - covar/(1-p1))
data.frame(X,Y)
}
David Duffy.
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From: Eric Pante [EMAIL PROTECTED]
Dear Listers,
I emailed the list a few days ago about how to bootstrap a community
matrix (species by sites) and get a consensus tree with node support. A
friend pointed out that a similar question remained unanswered in 2004.
I wish to re-word my
.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v
Even then, summary(m1) gives the same problem (as it refits). There is
separation in the data, of course, but I presume the ordinality gives
some extra information.
David Duffy.
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://math.cl.uh.edu/thompsonla/
under An S Manual to Accompany Agresti's Categorical Data Analysis 2nd ed.
(2002) along with Agresti's book itself.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
academic libraries.
David Duffy.
* Don't you use Pap or JPap at Myriad?
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disequilibria.
Note that haplo.stats and hapassoc are aimed specifically at comparing
groups or testing for association to other traits. My package
gllm is not as easy to use but can combine phased and unphased data in
loglinear models -- you could probably use cat in the same way.
David Duffy.
| David
] 1.3702710894887480597e-297
cf 1.37027108948832580215549799419452388134616261215463681945E-297
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research
I couldn't resist adding a more literal answer
unback - function(x) {
chars - unlist(strsplit(deparse(x),))
chars - chars[-c(1,length(chars))]
paste(gsub(,/,chars),collapse=)
}
unback(\n)
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED
(geno)$unique.alleles
As documented, this is R specific.
| David Duffy (MBBS PhD) email: [EMAIL PROTECTED] ,-_|\
| ph: INT+61+7+3362-0217 fax: -0101 / *
| Genetic Epidemiology Lab, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd
at the related loglinear models.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG
factor model based on polychoric correlations should fit perfectly, if
the no higher order interaction assumption is right,
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland
=.)
}
new.x[this.rec,3]-case[i]
}
new.x
}
David Duffy.
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routine to analyse them. The programs by Jing hua Zhao, Beth
Atkinson and others could also then be used for linkage analysis of
survival data (http://www.ucl.ac.uk/~rmjdjhz/r-progs.htm) (I haven't any
experience with these programs yet).
David Duffy.
| David Duffy (MBBS PhD
Trenkler, Dietrich said:
I found the following strange behavior using qnorm() and pnorm():
x-8.21;x-qnorm(pnorm(x))
[1] 0.0004638484
x-8.28;x-qnorm(pnorm(x))
[1] 0.07046385
x-8.29;x-qnorm(pnorm(x))
[1] 0.08046385
x-8.30;x-qnorm(pnorm(x))
[1] -Inf
qnorm(1-.Machine$double.eps)
[1]
I presume I am not alone in receiving return-to-sender mailings provoked
by a well known virus eg
[EMAIL PROTECTED]
(reason: 550 [EMAIL PROTECTED]... User unknown)
[EMAIL PROTECTED]
(reason: 550 [EMAIL PROTECTED]... User unknown)
[EMAIL PROTECTED]
(reason: 550 [EMAIL PROTECTED]...
Jens Oehlschlägel asked:
Can someone point me to literature and/or R software to solve the following
problem:
Assume n true scores t measured as x with uncorrelated errors e , i.e.
x = t + e
and assume each true score to a have a certain amount of correlation with
some of the other true
in f3xact. This problem should not occur.
The integer hash key is bigger than the largest allowable integer,
and so appears as a negative number. Table is too big.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v
website, one for
sequential analysis IIRC. I have some on my website for genetic
association (TDT and case-control) and linkage (variance components)
analysis.
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101
this -- see statlib or his
home page (there are several similar routines eg AS164). It would be
straightforward to write an R interface.
David Duffy
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package does this:
summary(brlr(V2 ~ V1))
brlr(formula = V2 ~ V1)
Coefficients:
Value Std. Error t value
(Intercept) 0.2620 1.0624 0.2466
V1 1.4014 1.0077 1.3908
Deviance: 3.5078
Penalized deviance: 3.528
Residual df: 7
--
| David Duffy (MBBS PhD
If your datasets are small, then it is not difficult to roll your own
using optim(). If you look at
http://www.qimr.edu.au/davidD/sib-pair.R
you will find such a routine at lines 1511-1562. This calls
kinship.rel() that produces NRM etc.
--
| David Duffy (MBBS PhD
the data.frame...
perhaps as.data.frame.table(table(spell,loc))
--
| David Duffy (MBBS PhD) ,-_|\
| email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / *
| Epidemiology Unit, Queensland Institute of Medical Research \_,-._/
| 300 Herston Rd, Brisbane
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