Hi all,
Does anyone have experience estimating the sample size for beta
regression? I have three treatment groups with 0.6, 0.5 and 0.3 mean of
proportions. I tried use BetaPASS but failed,
Regards,
Greg
[[alternative HTML version deleted]]
__
Hi Marc:
Thank you for your help in this matter.
With thanks
Abou
On Tue, Aug 10, 2021, 9:28 AM Marc Schwartz wrote:
> Hi,
>
> A search would suggest that there may not be an R function/package that
> provides power/sample size calculations for the specific scenarios that
> you are describi
Hi,
A search would suggest that there may not be an R function/package that
provides power/sample size calculations for the specific scenarios that
you are describing. There may be something that I am missing, and there
is also other dedicated software such as PASS
(https://www.ncss.com/softw
Hi Marc:
First, thank you very much for your help in this matter.
Will perform an initial omnibus test of all three groups (e.g. 3 x 2
chi-square), possibly followed by
all possible 2 x 2 pairwise comparisons (e.g. 1 versus 2, 1 versus 3,
2 versus 3),
We can assume *either* the desired sample s
Hi,
You are going to need to provide more information than what you have
below and I may be mis-interpreting what you have provided.
Presuming you are designing a prospective, three-group, randomized
allocation study, there is typically an a priori specification of the
ratios of the sample s
Dear All: good morning
*Re:* Sample Size Determination to Compare Three Independent Proportions
*Situation:*
Three Binary variables (Yes, No)
Three independent populations with fixed sizes (*say:* N1 = 1500, N2 = 900,
N3 = 1350).
Power = 0.80
How to choose the sample sizes to compare th
> Thanks for the suggestion but I'm not sure that it answers my original
> question.I need to know how many samples I need to collect to collect in
> order to estimate the sample size needed to achieve a specific margin of
> error for confidence intervals for the population variance. I'm not sure
Thanks for the suggestion but I'm not sure that it answers my original
question.I need to know how many samples I need to collect to collect in order
to estimate the sample size needed to achieve a specific margin of error for
confidence intervals for the population variance. I'm not sure wheth
On Tue, 2 Jul 2019 22:23:18 + (UTC)
Thomas Subia via R-help wrote:
> Colleagues,
> Can anyone suggest a package or code which might help me calculate
> the minimum sample size required to estimate the population variance?
> I can do this in Minitab but I'd rather do this in R. Thomas Subia
Y
just 1 but it will be zero.Hope this helps,Rui Barradas Enviado
a partir do meu smartphone Samsung Galaxy. Mensagem original
De: Thomas Subia via R-help Data:
02/07/2019 23:23 (GMT+00:00) Para: r-help@r-project.org Assunto:
[R] Sample size required to estimate populatio
homas Subia via R-help
Data: 02/07/2019 23:23 (GMT+00:00) Para:
r-help@r-project.org Assunto: [R] Sample size required to estimate population
variance Colleagues,Can anyone suggest a package or code which might help me
calculate the minimum sample size required to estimate the population varianc
Does this help?
https://www.r-bloggers.com/computing-sample-size-for-variance-estimation/
On Wed, 3 Jul 2019 at 10:23, Thomas Subia via R-help
wrote:
> Colleagues,
> Can anyone suggest a package or code which might help me calculate the
> minimum sample size required to estimate the population v
Colleagues,
Can anyone suggest a package or code which might help me calculate the minimum
sample size required to estimate the population variance? I can do this in
Minitab but I'd rather do this in R.
Thomas Subia
[[alternative HTML version deleted]]
___
Sounds like a homework problem. This list has a no homework policy if it is.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Sep 4, 2017 at 10:31
Hi
In R,how to do sample size calculation for three-way incomplete block
crossover study where within subject residual standard deviation,treatment
difference and power is given.
Thanks in advance.
Regards
Jose
[[alternative HTML version deleted]]
__
Or power.t.test()
-pd
> On 12 Apr 2017, at 18:44 , Bert Gunter wrote:
>
> Search "sample size power" on rseek.org. Many useful hits, including
> "samplesize" package.
>
> -- Bert
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
> and sticking thin
Search "sample size power" on rseek.org. Many useful hits, including
"samplesize" package.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Apr 12
> On Apr 12, 2017, at 3:20 AM, Jomy Jose wrote:
>
> In R how to calculate sample size,where power,residual standard deviation
> and treatment difference is given.?
Use the non-central t-distribution. The help page has further advice:
?pt
>
> [[alternative HTML version deleted]]
Pleas
In R how to calculate sample size,where power,residual standard deviation
and treatment difference is given.?
[[alternative HTML version deleted]]
__
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https://stat.ethz.ch/mailman/
Hi All,
What formula can I use to determine the right sample size for clustering
analysis with 100-300 variables?
What sampling methodology can be used for k-means or hierarchical clustering on
categorical fields so that all values of the categorical fields are included in
the sample?
Thanks
Hello,
At an R prompt, type
?power.t.test
Hope this helps,
Rui Barradas
Em 06-06-2013 20:58, Rebecca Greenblatt escreveu:
Looking to determine sample sizes for both my experimental and control
groups (I want only a small portion of my participants in my experimental
condition) in order to co
This is a duplicate question, right?
On Jun 6, 2013, at 12:58 PM, Rebecca Greenblatt wrote:
> Looking to determine sample sizes for both my experimental and control
> groups (I want only a small portion of my participants in my experimental
> condition) in order to compare population means. I wou
Looking to determine sample sizes for both my experimental and control
groups (I want only a small portion of my participants in my experimental
condition) in order to compare population means. I would be able to
estimate standard deviation beforehand.
I'm using the bpower function from the Hmisc
.@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Shane Carey
> Sent: Friday, April 26, 2013 1:09 PM
> To: Rui Barradas
> Cc: r-help@r-project.org
> Subject: Re: [R] sample size in box plot labels
>
> This works, great. Cheers
>
>
> On Fri, Apr 2
This works, great. Cheers
On Fri, Apr 26, 2013 at 12:02 PM, Rui Barradas wrote:
> Hello,
>
> To count the sample sizes for each factor try
>
> tapply(DATA$K_Merge, DATA$UnitName_1, FUN = length)
>
>
> Hope this helps,
>
> Rui Barradas
>
> Em 26-04-2013 10:48, Shane Carey escreveu:
>
> Hi,
>>
>
Hello,
To count the sample sizes for each factor try
tapply(DATA$K_Merge, DATA$UnitName_1, FUN = length)
Hope this helps,
Rui Barradas
Em 26-04-2013 10:48, Shane Carey escreveu:
Hi,
I would like to put the sample number beside each lable in a boxplot.
How do I do this? Essentially, I need
Hi
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Shane Carey
> Sent: Friday, April 26, 2013 11:49 AM
> To: r-help@r-project.org
> Subject: [R] sample size in box plot labels
>
> Hi,
>
>
Hi,
I would like to put the sample number beside each lable in a boxplot.
How do I do this? Essentially, I need to count the sample size for each
factor, see below:
Thanks
boxplot(DATA$K_Merge~factor(DATA$UnitName_1),axes=FALSE,col=colours)
title(main=list("Tukey Boxplot by Geology:\n K(%)",cex=c
Hello,
Lets assume I have an ordinal response variable representing the
D<-c(D0,D1,D2,D3,D4) where D0 is no damage and D4 is collapse which I want
to correlate with a continuous predictor variable, wind speed at the
location of each building.
is there a function in R which I can use to es
Hi,
I'm trying to determine a sample size calculation for a mock RCT. I want to
compare the event rate (proportion) between two unequal groups.
Thanks!
--
View this message in context:
http://r.789695.n4.nabble.com/Sample-Size-Calculation-tp4098429p4098429.html
Sent from the R help mailing l
From: https://stat.ethz.ch/pipermail/r-help/2011-November/294329.html
> I'm trying to compute sample size requirements for a binomial exact test.
> we want to show that the proportion is at least 90% assuming that it is
> 95%, with 80% power so any asymptotic approximations are out of the
> quest
I'm trying to compute sample size requirements for a binomial exact test.
we want to show that the proportion is at least 90% assuming that it is
95%, with 80% power so any asymptotic approximations are out of the
questions. I was planning on using binom.test to perform the simple test
against a
Hello Everyone,
I need to perform a sample size calculation using a drop the loser/keep the
winner design. I've been searching for examples of how to do this using R but
haven't found much.
The most promising possibility thus far is an R function called DrpLsrNRst.
This appears in the book
but I am confused a little
Karl
- Ursprüngliche Mail
Von: David Winsemius
An: Karl Knoblick
CC: Greg Snow ; "r-h...@stat.math.ethz.ch"
Gesendet: Samstag, den 13. August 2011, 2:18:37 Uhr
Betreff: Re: [R] Sample size AUC for ROC curves
On Aug 11, 2011, at 5:50 AM, Kar
- Ursprüngliche Mail
Von: Greg Snow
An: Karl Knoblick ; "r-h...@stat.math.ethz.ch"
Gesendet: Dienstag, den 9. August 2011, 19:45:12 Uhr
Betreff: RE: [R] Sample size AUC for ROC curves
If you know how to generate random data that represents your null
hypothesis
(chance, auc=0.5) and
Von: Greg Snow
An: Karl Knoblick ; "r-h...@stat.math.ethz.ch"
Gesendet: Dienstag, den 9. August 2011, 19:45:12 Uhr
Betreff: RE: [R] Sample size AUC for ROC curves
If you know how to generate random data that represents your null hypothesis
(chance, auc=0.5) and how to do your anal
nces@r-
> project.org] On Behalf Of Karl Knoblick
> Sent: Monday, August 08, 2011 3:29 PM
> To: r-h...@stat.math.ethz.ch
> Subject: [R] Sample size AUC for ROC curves
>
> Hallo!
>
> Does anybody know a way to calculate the sample size for comparing AUC
> of ROC
> curves a
Hallo!
Does anybody know a way to calculate the sample size for comparing AUC of ROC
curves against 'by chance' with AUC=0.5 (and/or against anothe AUC)?
Thanks!
Karl
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R-help@r-project.org mailing list
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PL
Awesome! Thanks, David and Dennis! And now I know how to search for
packages more effectively.
Tom
On Mon, Apr 4, 2011 at 9:38 PM, Dennis Murphy wrote:
> Start here:
>
> library(sos) # install first if necessary
> findFn('sample size survey')
>
> I got 238 hits, many of which could be relev
Start here:
library(sos) # install first if necessary
findFn('sample size survey')
I got 238 hits, many of which could be relevant.
HTH,
Dennis
On Mon, Apr 4, 2011 at 6:05 PM, Thomas Levine wrote:
> Hi,
>
> Is there an R package for estimating sample size requirements for
> parameter esti
Hi,
Is there an R package for estimating sample size requirements for
parameter estimation in sample surveys? In particular, I'm interested
in sample size estimation for stratified and systematic sampling. I
have a textbook with appropriate formulae, but it'd be nice if I
didn't have to type in al
t.org] On Behalf Of Lao Meng
> Sent: Monday, March 21, 2011 1:20 AM
> To: R help
> Subject: [R] Sample size of longitudinal and skewed data
>
> Hi all:
> I have a question about the sample size calculation.
>
> It's a pilot study,which includes 2 groups(low,high),3 t
Hi all:
I have a question about the sample size calculation.
It's a pilot study,which includes 2 groups(low,high),3 time point(3,6,9
monthes).Each person has 3 results which according to the
3 time points.So it's a longitudinal study.
I want to calculate the minimum sample size from the pilot st
did you try to fit your data with a skew-normal/skew-t distribution?
If that works, you can use simulation.
Kjetil
On Tue, Mar 15, 2011 at 2:31 AM, Lao Meng wrote:
> Hi all:
> I have a question on sample size calculation of 2 groups of data. If 2
> groups of data are all normal distribution, the
Hi all:
I have a question on sample size calculation of 2 groups of data. If 2
groups of data are all normal distribution, then I can use the function
"n.indep.t.test.eq" from samplesize package.But if 2 groups of data are all
skewed distribution, but not normal distribution,how can I calculate the
On Nov 20, 2010, at 8:31 AM, XINLI LI wrote:
> Dear R users:
>
> How to calculate the sample size with ANCOVA? For example, in a
> clinical trial, the correlation between the baseline and one-year follow-up
> blood pressure is 0.7, with a standrad devision 15, in order to detect a 10
> d
Dear R users:
How to calculate the sample size with ANCOVA? For example, in a
clinical trial, the correlation between the baseline and one-year follow-up
blood pressure is 0.7, with a standrad devision 15, in order to detect a 10
difference between baseline and follow-up with a power = 0
So that a bit lower than the 77 above but
implies that 42,207 would be needed.
--
David.
>
> Thanks a lot everybody again for your suggestions,
> if anybody has other comments, they are always welcome.
>
> Best,
>
> Giulio
>
>
> > Subject: Re: [R] Sample size c
ybody again for your suggestions,
if anybody has other comments, they are always welcome.
Best,
Giulio
> Subject: Re: [R] Sample size calculation for differences between two very
> small proportions (Fisher's exact test or others)?
> From: marc_schwa...@me.com
> Date: Mon, 8 Nov
Hi,
I don't have access to the article, but must presume that they are doing
something "radically different" if you are "only" getting a total sample size
of 20,000. Or is that 20,000 per arm?
Using the G*Power app that Mitchell references below (which I have used
previously, since they have a
On Nov 8, 2010, at 11:16 AM, Mitchell Maltenfort wrote:
Not with R,
Really?
require(sos)
findFn("power exact test")
found 54 matches; retrieving 3 pages
2 3
These look on point:
http://finzi.psych.upenn.edu/R/library/statmod/html/power.html
http://finzi.psych.upenn.edu/R/library/binom/htm
Not with R, but look for G*Power3, a free tool for power calc,
includes FIsher's test.
http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3
On Mon, Nov 8, 2010 at 10:52 AM, Giulio Di Giovanni
wrote:
>
>
> Hi,
> I'm try to compute the minimum sample size needed to have at least an 80% of
Hi,
I'm try to compute the minimum sample size needed to have at least an 80% of
power, with alpha=0.05. The problem is that empirical proportions are really
small: 0.00154 in one case and 0.00234. These are the estimated failure
proportion of two medical treatments.
Thomas and Conlon (1992)
On 09/27/2010 08:09 PM, Paul Miller wrote:
> Hello Everyone,
>
> I'm trying to conduct a couple of power analyses and was hoping
> someone might be able to help. I want to estimate the sample size
> that would be necessary to adequately power a couple of
> non-inferiority tests. The first would b
I haven't done much with the type of data you're working with, but
here is a post that lists a few packages for doing sample size
calculations in R. Perhaps one of them will be helpful.
https://stat.ethz.ch/pipermail/r-help/2008-February/154223.html
Andrew Miles
On Sep 27, 2010, at 2:09 PM,
Hello Everyone,
I'm trying to conduct a couple of power analyses and was hoping someone might
be able to help. I want to estimate the sample size that would be necessary to
adequately power a couple of non-inferiority tests. The first would be a
log-rank test and the second would be a Wilcoxon
The obvious:
Take a small sample, say 25-50. Get an estimate of your distribution
from that. Then use this to determine how many more (if any)
additional samples you need for desired precision. This latter can
probably easily be done via simulation/bootstrap if you don't want to
specify a paramet
Basically, we have a population of 4,392 documents and we want to find out
the number of patents per document. We don’t want to go through all 4,392
documents, but want a reliable sample size from which to draw inferences. I
feel like this count data will not follow a normal distribution, but more
On Jul 14, 2010, at 6:13 AM, Karl Knoblick wrote:
> Hallo!
>
> Does anyone know a possibility to perform a sample size estimation for an
> ANCOVA? Would be great!
>
>
> Thanks
> Karl
I don't know of a function in R that performs this directly. However, if you
Google:
http://lmgtfy.com/?
Hallo!
Does anyone know a possibility to perform a sample size estimation for an
ANCOVA? Would be great!
Thanks
Karl
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PLEASE do read the posting guide http://www.R-pr
Thanks Kevin. I thought the time t is at the end of follow-up (length of
follow-up)?
John
--- On Thu, 5/6/10, Kevin E. Thorpe wrote:
> From: Kevin E. Thorpe
> Subject: Re: [R] sample size for survival curves
> To: "array chip"
> Cc: r-help@r-project.org
> Date: Th
p1=0.8 and p2=0.6 at 5 years at 5%
significance level with 80% power"
any comments are appreciated.
Â
John
--- On Thu, 5/6/10, Joris Meys wrote:
From: Joris Meys
Subject: Re: [R] sample size for survival curves
To: "array chip"
Date: Thursday, May 6, 2010, 8:12 PM
On 05/06/2010 07:20 PM, Kevin E. Thorpe wrote:
array chip wrote:
Dear R users, I am not asking questions specifically on R, but I know
there are many statistical experts here in the R community, so here it
goes my questions:
Freedman (1982) propose an approximation of sample size/power
calculat
array chip wrote:
Dear R users, I am not asking questions specifically on R, but I know there are
many statistical experts here in the R community, so here it goes my questions:
Freedman (1982) propose an approximation of sample size/power calculation based
on log-rank test using the formula b
Dear R users, I am not asking questions specifically on R, but I know there are
many statistical experts here in the R community, so here it goes my questions:
Freedman (1982) propose an approximation of sample size/power calculation based
on log-rank test using the formula below (This is what n
Just to follow up on Bert's and Frank's excellent comments. I'm
continued to be amazed by people trying to interpret a single tree.
Besides the variability in the tree structure (try bootstrapping and see
how the trees change), it is difficult to make sense of splits more than
a few levels down (h
10 12:55 pm
Subject: Re: [R] sample size > 20K? Was: fitness of regression tree: how to
measure???
To: 'Frank E Harrell Jr' , 'vibha patel'
Cc: r-help@r-project.org
> Since Frank has made this somewhat cryptic remark (sample size > 20K)
> several times now, per
Good comments Bert. Just 2 points to add: People rely a lot on the tree
structure found by recursive partitioning, so the structure needs to be
stable. This requires a huge samples size. Second, recursive
partitioning is not competitive with other methods in terms of
predictive descriminatio
> Incidentally, there is nothing new or radical in this; indeed, John Tukey,
> Leo Breiman, George Box, and others wrote eloquently about this decades ago.
> And Breiman's random forest modeling procedure explicitly abandoned efforts
> to build simply interpretable models (from which one might infe
Since Frank has made this somewhat cryptic remark (sample size > 20K)
several times now, perhaps I can add a few words of (what I hope is) further
clarification.
Despite any claims to the contrary, **all** statistical (i.e. empirical)
modeling procedures are just data interpolators: that is, all t
Dear list members,
I am trying to estimate power/sample size based on already collected
pilot data.
The setting: Five orchards have been sampled with respect to fruit
damage. In each orchard two plots were selected (semi-randomly), where
one was treated and one left as control. Within each plot a
Dear Marc,
Thank you very much for the advice and the papers, it helps.
Regards,
Paul
From: >Marc Schwartz
To: "Prew, Paul"
Cc: r-help@r-project.org
Subject: Re: [R] Sample size for proportion, not binomial
Message-ID:
Content-Type: text/plain; charset=windows-1252
On Mar 23
On Mar 23, 2010, at 11:05 AM, Prew, Paul wrote:
> Hello, I am looking for a sample size function for samples sizes, to test
> proportions that are not binomial proportions. The proportions represent a
> ratio of (final measure) / (baseline measure) on the same experimental unit.
> Searches u
Hello, I am looking for a sample size function for samples sizes, to test
proportions that are not binomial proportions. The proportions represent a
ratio of (final measure) / (baseline measure) on the same experimental unit.
Searches using RSeek and such bring multiple hits for binomial prop
I would appreciate any help on this problem. I need to perform a sample size
analysis for a study comparing the performances of 2 different methods of
diagnostic classification. Assume that method 1 has an accuracy of p1
against known truths (a reference classification, as multiple categories),
an
ath.ethz.ch
Gesendet: Dienstag, den 26. Mai 2009, 16:43:09 Uhr
Betreff: Re: [R] Sample size calculation proportions with EpiR: Discrepancy to
other calculators
On Tue, 26 May 2009, Chuck Cleland wrote:
> On 5/26/2009 2:53 AM, Karl Knoblick wrote:
>> Hallo!
>>
>> I have done a sam
Karl Knoblick wrote:
Hallo!
Does anybody know how to calculate a sample size estimation for proportions
with continuity correction?
That would lose power.
Frank
I only found EpiR which seems to calculate without continuity correction:
library(epiR)
epi.studysize(treat = .65, control = .
Hallo!
Does anybody know what epiR calculates with method = "survival"?
library(epiR)
library(survival)
epi.studysize(treat = .65, control = .50, n = NA, sigma = NA,
power = 0.80, r = 1, conf.level = 0.95, sided.test = 2, method = "survival")
Because I found out that method "proportion" does n
Hallo!
Does anybody know how to calculate a sample size estimation for proportions
with continuity correction?
I only found EpiR which seems to calculate without continuity correction:
library(epiR)
epi.studysize(treat = .65, control = .50, n = NA, sigma = NA,
power = 0.80, r = 1, conf.level
On Tue, 26 May 2009, Chuck Cleland wrote:
On 5/26/2009 2:53 AM, Karl Knoblick wrote:
Hallo!
I have done a sample size calculation for proportions with EpiR. The input is:
treatment group rate p=0.65
control group rate p=0.50
significance level 0.95
power 0.80
two-sided
ration group 1 and 2: 1.
On 5/26/2009 2:53 AM, Karl Knoblick wrote:
> Hallo!
>
> I have done a sample size calculation for proportions with EpiR. The input is:
> treatment group rate p=0.65
> control group rate p=0.50
> significance level 0.95
> power 0.80
> two-sided
> ration group 1 and 2: 1.0
>
> I have done this in t
Hallo!
I have done a sample size calculation for proportions with EpiR. The input is:
treatment group rate p=0.65
control group rate p=0.50
significance level 0.95
power 0.80
two-sided
ration group 1 and 2: 1.0
I have done this in the following way:
library(epiR)
epi.studysize(treat = 0.65, cont
Thanks. I did the search before I posted and found those threads.
However, it does not seem to do what I want. All I want to do is
estimate the sample size for a point estimate, not do a GLM. I just
want the mean within a margin of error, and to a given CI.
I've tried writing some code to do
The notion that you can just add or subtract 0.03 from estimate is
obviously incorrect.
Presuming you meant to call you lower bound q05 and the upper bound
q95, the numbers I get are in your 10,000 iteration loop are 4.97 and
5.18 (around a mean of 5.08). So roughly a .1 swing on each side
The first hit for search on "sample size" and "poisson" on Baron's
search engine web interface appears on target:
http://search.r-project.org/cgi-bin/namazu.cgi?query=%22sample+size%22+poisson&max=100&result=normal&sort=score&idxname=functions&idxname=Rhelp02a
Getting the same result from your
Is there a function in R that will allow me to estimate the sample
size required from count data (poisson data?), given the known
variance and desired margin of error and confidence interval?
My specific data set will be based on a survey of hikers that will be
asked about the number of anim
> > -Original Message-
> > > From: [EMAIL PROTECTED]
> > > [mailto:[EMAIL PROTECTED] On Behalf Of Zaihra T
> > > Sent: Wednesday, March 26, 2008 7:57 AM
> > > To: Jan T. Kim; R-help@r-project.org
> > > Subject: ! [R] sample size in
Hallo!
I found a question exactly as mine, but I did not found an answer. Therefore I
post this again - hopefully there will be an answer!
Thanks in advance!
karl
From: Berta
Date: Tue, 27 Feb 2007 18:58:48 +0100
Hi R-users,
I want to calculate the sample size needed to carry out a 2-sample
p
Essioux, Laurent wrote:
> Hi everyone,
>
> I was wondering whether extension of the current spower function for
> Hmisc were existing?
>
> My current focus is to calculate sample size based on the log-rank test
> with more than 2 groups (with/without trend)
>
> Taking into account the loss of fo
Hi everyone,
I was wondering whether extension of the current spower function for
Hmisc were existing?
My current focus is to calculate sample size based on the log-rank test
with more than 2 groups (with/without trend)
Taking into account the loss of follow up and the accrual processes.
A SPSS
6 AM
To: Nordlund, Dan (DSHS/RDA); Jan T. Kim; R-help@r-project.org
Subject: Re: [R] sample size in bootstrap(boot)
Hi Dan,
Thanks for response yes i do know that bootstrap samples generated by
function boot are of the same size as original dataset but s
"Nordlund, Dan (DSHS/RDA)" wrote:
> > -Original Message-
> > From: [EMAIL PROTECTED]
> > [mailto:[EMAIL PROTECTED] On Behalf Of Zaihra T
> > Sent: Wednesday, March 26, 2008 7:57 AM
> > To: Jan T. Kim; R-help@r-project.org
> >
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Zaihra T
> Sent: Wednesday, March 26, 2008 7:57 AM
> To: Jan T. Kim; R-help@r-project.org
> Subject: [R] sample size in bootstrap(boot)
>
>
>Hi,
>
>Can some
Hi,
Can someone tell me how to control sample size (n) in bootstrap function
boot in R. Can we give some option like we give for # of repeated
samples(R=say 100).
Will appreciate any help.
thanks
__
R-help@r-project.org mailing
Hello!
Is there a possibilty in R to calculate the sample size for evaluation of
reference values? Especially reference values with a covariate age and a factor
gender?
Any help will be appreciated.
Thanks!
Karl
Heute schon einen Blick in die Zukunft von E-Mails wagen?
Hi for all.
How can I determinate in R the sample size to estimate a logistic
regression with two outcomes. One of outcomes was 47% in population
and I want determine the factors that influence that probability.
Thanks everyone
__
R-help@r-project
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