Hello
I have created a graph using the following commands:
<<<
startBReP3O1T <- diffs$BReP3O1T - diffs$diff_BReP3O1T
endBReP3O1T <- diffs$BReP3O1T
x <- seq(47,89, length = 10)
ymin <- min(min(startBReP3O1T), min(endBReP3O1T))
ymax <- max(max(startBReP3O1T), max(endBReP3O1T))
y <- seq(ymin, ymax,
Hello
I wrote a simple program to modify a boxplot:
<<<
gdsbox <- function(indvar){
boxplot(indvar~gds3lev,
main = paste('Boxplot of', substitute(indvar), "for GDS groups"),
names = c('1', '3', '4, 5, 6'))
}
>>>
If I attach the dataframe gdsgraph, this works fine. However, I've been war
Good morning
I recently shifted to digest mode; I get the digest each day (sometimes two in
a day) and when I open the first file
it opens as a text file with a list of topics; but then it is hard to find the
right message. In a list of 100 or so links,
counting to find link number 53 or whatev
Good afternoon
Using R 2.9.2 on a machine running Windows XP
I have a longitudinal data set, with data on schools and their test scores over
a four year period. I have centered year, and run the following
m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_,
data = long,
Hello
Running R2.9.2 on Windows XP
I am puzzled by the performance of LME in situations where there are missing
data. As I understand it, one of the strengths of this sort of model is how
well it deals with missing data, yet lme requires nonmissing data.
Thus,
m1.mod1 <- lme(fixed = math_
I wrote
>>> I am puzzled by the performance of LME in situations where there are
>>> missing data. As I
>>> understand it, one of the strengths of this sort of model is how well it
>>> deals with missing
>>> data, yet lme requires nonmissing data.
>
Mark Difford replied
>You are confusing mi
Paul Smith wrote
>
>Is there some way of drawing a boxplot, with R, when one does not have
>the original continuous data, but only the data grouped in classes?
>The function boxplot() can only deal with original data.
It's not clear how the data are, now. What are the classes? Are they numbers?
Frank E Harrell Jr wrote
>Ben Bolker wrote:
>>
>>
>> Allan.Y wrote:
>>> Hi everyone,
>>>
>>> I am wondering if there exists a stepwise regression function for the
>>> Bayesian regression model. I tried googling, but I couldn't find
>>> anything. I know "step" function exists for regular stepwi
Ravi Varadhan wrote
>
>I have heard this (i.e. only head-to-head comparisons are valid) and various
>other folklores about AIC and BIC based model selection before, including
>one that these information criteria are only applicable for comparing two
>nested models.
>
>Where has it been demonstra
Fran100681 wrote
>
>just a simple question
>
>How can I do to invert the sign of a number? (for example: -4 to 4, 2 to -2
>and so on..)
>I was looking for a specific function in R but I didn't found it...
>thank you
>
Is there something wrong with *-1 ?
Peter
Peter L. Flom, PhD
Statistical Cons
David Winsemius wrote
>I always assumed that the intercept was zero and the slope = unity.
>
> y <- rt(200, df = 5)
> qqnorm(y); qqline(y, col = 2)
> qqplot(y, rt(300, df = 5))
> abline(0, 1, col="red")
>
Suppose you have the following
x <- rnorm(500)
y <- 500*(x + runif(500, 0,1))
qqplot(x,
carol white wrote
>So the conclusion is that abline(0,1) should always be used and if it doesn't
>go through the qqplot, the two distributions are not similar?
I think it depends what you mean by "similar". E.g., if you mean "are both of
these distributions (e.g.) normal?" then abline(0,1) is
John Fox wrote
>
>I assumed that Carol wanted to compare the shapes of the distributions and
>to adjust for differences in centre and spread. To put a line through the
>quartiles or to base a line on the medians and IQRs is more robust than
>using the means and sds.
>
Hi John
Indeed it is.
It al
Peter Ehlers wrote
>
>That's not what qqline() does and for good reason - it treats
>x and y asymmetrically.
>
>But qqline() is a very simple function, using the quartiles
>as also suggested by John. Here's a modified version that
>should work for Carol:
>
>qqline2 <- function (x, y, ...)
>{
>
Good morning
I am learning about NLME and LME4, using Pinheiro and Bates and other materials
from Douglas Bates, but I have not seen anything on how to do variable
selection sensibly in this type of model.
In OLS regression, I frequently use the lasso, but googling did not reveal a
method for
Good morning
I just got a new computer with Windows 7. R works fine, but the editor I am
used to using "RWinEdt" does not. I did find one blog post on how to get
RWinEdt to work in Windows 7, but I could not get those instructions to work
either.
Is there a patch for RWinEdt?
If not, is the
Good morning
I am having problems with the latex function for an ols model from the Design
library.
When I run:
dd <- datadist(bp3)
options(datadist = 'dd')
spline1 <- ols(data = bp3, AORSP~rcs(Age,3)*P1 + Htm + WtKg + HR + AORMAP)
spline1
everything is as expected.
But when I try
latex(spl
Please xcuse me for being slightly off-topic and cross-posting
I have a data set of schools, with scores for 4 years. The goal is to evaluate
the effect of an intervention on the scores, accounting for some covariates
which are not problematic. The chief problem is that the intervention could
Arnab Maity wrote
>
>
>
>I like to call R from SAS. Could you please help me?
>
There are two methods that I know of:
1) Phil Rack has written a program called A Bridge to R see:
http://minequest.com/WordPress/?p=102
2) If you have SAS/IML licensed, you can link to R through IML studio. I
Trafim wrote
>
>well, I definitely don't understand anything.
>Why the hist function with freq=FALSE gives such a strange result???
>
>R <- c(-1.10, 0.79, -1.17, -0.53, -0.26, -0.22, 0.29, -0.26, -0.26, 0.39)
>hist(R, freq=FALSE, breaks=10)
>
The total AREA has to equal 1, which does not mea
Good afternoon
Running R2.10.0 on Windows
I have a data frame that includes (among much else) a factor (In_2006) and a
continuous variable (math_3_4). I would like to find the 2 cases for In_2006 =
0 that are closest to each case where In_2006 = 1.
My data looks like
In_2006 math_3_4
David Winsemius wrote
>
>On Dec 2, 2009, at 3:01 PM, Peter Flom wrote:
>
>> Good afternoon
>>
>> Running R2.10.0 on Windows
>>
>> I have a data frame that includes (among much else) a factor
>> (In_2006) and a continuous variable (math_3_4). I wo
Thanks Chuck
I did not know about that MatchIt. I will check it out
Peter
-Original Message-
>From: Chuck Cleland
>Sent: Dec 2, 2009 3:47 PM
>To: Peter Flom
>Cc: r help
>Subject: Re: [R] Finding cases in one subset that are closet to another subset
>
>On 12/
Knut Krueger wrote
>
>I think this is more an general question to GLMs.
>
>The result was better in all prior GLMs when I admitted the non
>significant factors, but this is the first time that the result is worse
>than before. What could be the reason for that?
>
>glm(data1~data2+data3+data4+data5
Wacek Kusnierczyk wrote
>> Seriously? You think:
>>
>> lapply(1:n, rnorm, 0, 1)
>>
>> is 'clearer' than:
>>
>> x=list()
>> for(i in 1:n){
>> x[[i]]=rnorm(i,0,1)
>> }
>>
>> for beginners?
>>
>> Firstly, using 'lapply' introduces a function (lapply) that doesn't
>> have an intuitive name. Also,
I wrote
As a beginner, I agree the for loop is much clearer to me.
Wacek Kusnierczyk replied
>
>well, that's quite likely. especially given that typical courses in
>programming, afaik, include for looping but not necessarily functional
>stuff -- are you an r beginner, or a programming
Dieter Menne wrote
>Technically a good point, but I found it helpful for starters who want to
>avoid the inferno of "what's attached now?" not to use it at all.
>My suggestion is to use with() instead because it has a higher locality.
>
>I know, many of the examples use attach.
As a beginner,
utkarshsinghal wrote
>> Hi all,
>>
>> I am performing a stepwise regression by running the "step" function on an
>> "lm" object. Now I want to save the intermediate iterations. I know the
>> argument trace=T will print it on the console, but I rather want to assign
>> it to some R object or may b
charles78 wrote
>I have a stupid question on how to get the real p-values for wilcox.test and
>correlation. the minmun can be reached is 2.2E-16 using the R version
>2.6.2. I do not think it is the R version causing this but other issues.
>
>Any help is highly appreciated.
>
Can I ask why you
Jean-Paul Kibambe Lubamba wrote
>
>I have two questions:
>
>I am computing a linear regression model with 0 as Intercept.
>
>Well, I would like the sum of my predicted values be equal to a constant
>and therefore analyze if my coefficients are significatively different
>using or not this constrain
I use WinEct, which is shareware and has a variation just for R, called RWinEdt.
Peter
-Original Message-
>From: Mike Lawrence
>Sent: Jun 2, 2009 7:51 AM
>To: rhelp
>Subject: Re: [R] Most used R editors
>
>I'm on Mac OS X and I've been using TextMate, though I feel guilty
>that it's non
Frank E Harrell Jr wrote
>Armida,
>
>I regret putting CTABLE as an option on the old SAS PROC LOGIS which was
>a basis for PROC LOGISTIC. Classification tables are arbitrary and
>misleading so I would stay away from them.
>
>You might build a model with and without the variable of interest and
Christophe Genolini wrote
>Thanks for yours answers. So if I understand:
> - Trajectories are continuous, the other are discrete.
> - The difference between time series and longitudinal is that time
>series are made at regular time whereas longitudinal are not ?
> - Repeated measures are over a
Lindsay Banin wrote
>Hi there,
>
>I am looking to compare nonlinear mixed effects models that have different
>nonlinear functions (different types of growth curve)embedded. Most of the
>literature I can find focuses on comparing nested models with likelihood
>ratios and AIC. Is there a way to c
Chunhao Tu wrote
>Hi R users,
>My question is, If I have 3 groups, A, B, C and I know mean of A =20, B=21,
>and C=20.5 and I also know the
>standard error of A =1.1, B=2.2, C=3.2. Plus, I know A has 30 observations,
>B has 78, C has 45. But I do not have the raw data.
>
>Can I use pairwise.t.tes
Werner Wernersen wrote
>Hi,
>
>I am trying to specify a multinomial logit model using the multinom function
>from the nnet package. Now I add another independent variable and it halves
>the AIC as given by summary(multinom()). But when I call Anova(multinom())
>from the car package, it tells me
Patrick Burns wrote
>Proposal
>
>That a new mailing list be established
>that pertains exclusively to R documentation.
>The purpose of the list would be to discuss
>weak sections of the documentation and
>establish fixes for those weak spots.
>
>
>Pro
>
>If it works, there would be better documen
ostatistics and Informatics
>>> University of Maryland School of Medicine Division of Gerontology
>>> Baltimore VA Medical Center
>>> 10 North Greene Street
>>> GRECC (BT/18/GR)
>>> Baltimore, MD 21201-1524
>>> (Phone) 410-605-7119
>>> (
I certainly don't have anything against the WIKI, but I think that the
documentation
is where the action is, especially for newbies. It's the natural first step
when you want to learn about a function or when you get an error message you
don't understand.
Peter
Peter L. Flom, PhD
Statistical
Well, suppose I wanted to suggest changes to some documentation, or write an
alternate help file for some function. Where would I put it?
Let's say I type, in R, ?median. Now suppose I have suggestions. If I look at
http://wiki.r-project.org/rwiki/doku.php?id=&idx=rdoc:base
I don't see the m
"Carlos J. Gil Bellosta" wrote
>
>I had a conversation with a guy working in a "business intelligence"
>department at a major Spanish bank. They rely on recursive partitioning
>methods to rank customers according to certain criteria.
>
>They use both SAS EM and Salford Systems' CART. I have used
>Dieter Menne wrote:
>>
IF TYPE='TRUCK' and count=12 THEN VEHICLES=TRUCK+((CAR+BIKE)/2.2);
>>> vehicles <- ifelse(TYPE=='TRUCK' & count=12, TRUCK+((CAR+BIKE)/2.2), NA)
>>>
>>>
>>
>> Read both versions to an audience, and you will have to admit that this is
>> one of the cases where SAS is su
drmh wrote
>
>Hello again,
>In my situation, I have three variables: pretest, posttest, and cohesion.
>
>I want to work out the correlation between postest and cohesion.
>
cor(cohesion, posttest) gives you this.
>I looked at multiple sets of data and created ANOVA tables of them. However,
>as
carol white wrote
>Consider a vector of 100 elements (attached files). then,
>
>truehist(b)
>lines(density(b[20:50]))
>
>How is it possible to have density plots of all subsets like b[20:50] within
>histogram (without exceeding the max of historgram on y axis)?
>
I didn't open your attached fi
Dieter Menne wrote
>I noted the "and" was misleading. Read: Good journals like Lancet,
>New English and many British Journal of XXX really help you to do
>better.
I am one of the statistical editors for PLoS Medicine, and I try to help
people do better; often, the people take my advice. Somet
Steve Murray wrote
>
>I have a data frame of the nature:
>I am hoping to plot columns 2 and 3 against Latitude. I understand that you
>have to do this by plotting one column at a time, so I have been starting by
>attempting the following, but receiving errors:
>
>
>I'm obviously doing someth
Steve Murray wrote
>
>I'm attempting to insert a legend into a line graph. I've sorted out the
>positioning, but I'm unable to display the sample line and associated colour
>to go within the legend box. Instead, under the variable names, the numbers 1,
>2, 2, 3 are displayed in a column (with '
steve_fried...@nps.gov wrote
>
>I have encountered a situation with regards to plotting barcharts with
>associated error bars. My search for clues on how to accomplish this
>turned up some interesting information. Basically, I found that including
>error bars with barplots is not desirable and he
Simon Pickett wrote
>My institute uses SAS religiously, I am the only R "heathen".
>
>I have resisted learning to use SAS because I dont see the point after years
>of using R and I like being able to do everything using one program.
>However, my colleagues maintain that SAS is "better" for prog
Hello
Using R 2.7.0 on Windows.
I am running a linear discriminant analysis as follows
discrim1 <- lda(normvar~ mafmahal+ mrfmahal+ mffmahal+ bafmahal+ brfmahal+
cofmahal+ bmfmahal+ cfmahal+ fractmahal+ antmahal+ absmifmahal+
absifmahal, subset = train)
prediction <- predict(discri
I wrote (in part)
>
> I am running a linear discriminant analysis as follows
>
>
> discrim1 <- lda(normvar~ mafmahal+ mrfmahal+ mffmahal+ bafmahal+ brfmahal+
> cofmahal+ bmfmahal+ cfmahal+ fractmahal+ antmahal+ absmifmahal+
> absifmahal, subset = train)
> prediction <- predict(discr
I wrote
> Hello
>
> Using R 2.7.0 on Windows.
>
> I am running a linear discriminant analysis as follows
>
>
> discrim1 <- lda(normvar~ mafmahal+ mrfmahal+ mffmahal+ bafmahal+ brfmahal+
> cofmahal+ bmfmahal+ cfmahal+ fractmahal+ antmahal+ absmifmahal+
> absifmahal, subset = train)
Dear r-help
I am trying to run LDA on a training data set, and test it on another data set
with the same variables. I found examples using crossvalidation, and using
training and testing data sets set up with sample, but not when they are
preassigned.
Here is what I tried
# FIRST SET UP A DA
Hello again
I recently downloaded the gcl package, which "computes a fuzzy rules or tree
classifier from data". It is very interesting and is giving good results.
However, rather than return a list, it returns a function. Per the example in
the documentation:
library(gcl)
library(datasets)
Robin Williams wrote
Is there any facility in R to perform a stepwise process on a model,
which will remove any highly-correlated explanatory variables? I am told
there is in SPSS. I have a large number of variables (some correlated),
which I would like to just chuck in to a model and perform
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