Hello all,
I am using a glm() and would like to fix one of the regression coefficients
to be a particular value and see what happens to the fit of the model. E.g.:
mod1 <- glm(Y ~ X1 + X2,family='binomial')
mod2 <- glm(Y~[fixed to 1.3]X1 + X2,family='binomial')
The beta for X1 is freely estimate
differences?
On Fri, Sep 17, 2010 at 6:43 PM, Johan Jackson wrote:
> Hi all,
>
> I have major heterogeneity in variances across labs (100-fold). There is no
> apparent variance heterogeneity across y-hat. By using lme4 in the following
> way, am I accounting for the variance differences in la
Hi all,
I have major heterogeneity in variances across labs (100-fold). There is no
apparent variance heterogeneity across y-hat. By using lme4 in the following
way, am I accounting for the variance differences in labs?:
lmer(y ~ fixed1 + covariates + (fixed1|labs))
I'm not sure that it is - I t
t bites you on
your ass I guess.
JJ
On Wed, Aug 18, 2010 at 5:52 PM, David Winsemius wrote:
>
> On Aug 18, 2010, at 6:45 PM, Peter Ehlers wrote:
>
> On 2010-08-18 11:49, Johan Jackson wrote:
>>
>>> No, apologies (good catch David!), I merely copied the script
>>
data= argument?
JJ
On Wed, Aug 18, 2010 at 11:29 AM, David Winsemius wrote:
>
> On Aug 18, 2010, at 1:19 PM, Johan Jackson wrote:
>
> Hi all,
>>
>> Thanks for the replies (including off list). I have since resolved the
>> discrepant results. I believe it has to
t wrote:
> One difference is that the random effect in lmer is assumed --
> implicitly constrained, as I understand it -- to
> be a bell curve. The fixed effect model does not have that constraint.
>
> How are the values of "labs" effects distributed in your lm model?
Hello,
Setup: I have data with ~10K observations. Observations come from 16
different laboratories (labs). I am interested in how a continuous factor,
X, affects my dependent variable, Y, but there are big differences in the
variance and mean across labs.
I run this model, which controls for mean
HI all,
This is probably simple, but I haven't been able to locate the answer either
in the Import Manual or from searching the listserve.
I have tab-delimited data with different numbers of elements in each row. I
want to read it into R, such that R fills in "NA" in elements that have no
data. H
Hello Eric,
If you can do a project like this (that manages huge datasets) in SAS, I'd
recommend to just do them in SAS rather than use R. I've sadly come to the
conclusion that R isn't very good at working with large datasets, and until
the powers that be try to do something about to help users l
> If the main purpose is to circumvent R's memory requirements,
> then there have been plenty of posts on that issue.
>
> -Peter Ehlers
>
>
> Johan Jackson wrote:
>
>> "I suspect that you really don't know what 'raw' type means and haven't
#x27;re at it! Write
it out. Read it back in. Having problems? Then come talk to me...
JJ
On Thu, Feb 11, 2010 at 11:36 AM, Peter Ehlers wrote:
> Johan Jackson wrote:
>
>> Hi Don and all,
>>
>> I guess we're getting somewhere. Thanks. The file (first three columns,
&
t file raw" is, but
> the colClasses argument is to define whether the column will be treated
> as containing "factors", "logical", "integer" etc...
> For more on read.table, read the manual "R Data Import/Export" available
> on the R-project
rrect, it should work. The problem is somewhere
>> else, coming from your own file. Did you try skipping the colClasses
>> argument? To see how it looks like... If you can import it that way, try
>> str(x) to see what you have. It might help you.
>> 2) I've never h
Hi all,
First off, it is surprising that there are no examples of how to use
read.table() under ?read.table !
I am trying to read in a flat file of type 'raw'. It has 1000 rows and 600K
columns. I have the RAM to accomplish this, but can't get the data into R
using read.table:
x <- read.table("d
Dear stats experts:
Me and my little brain must be missing something regarding bootstrapping. I
understand how to get a 95%CI and how to hypothesis test using bootstrapping
(e.g., reject or not the null). However, I'd also like to get a p-value from
it, and to me this seems simple, but it seems no-
Hi all,
Simple question re k-means. If I have a data set with columns that are on
different scales (say col 1 has var=100 and col2 var=2), will this make a
difference to the k-means algorithm? It seems as though it does. If so,
should we first standardize the columns of the dataset so that each co
Hello,
Is there any way to add multiple separators in the sep= argument in
read.table? I would like to be able to create different columns if I see a
white space OR a "/".
Thanks in advance,
JJ
[[alternative HTML version deleted]]
__
R-help@r
I feel out of my league responding to a discussion among such an august
group of statisticians. But I think I can maybe provide some insight from
someone who migrated from SPSS into R and learned R on my own.
I must say that I found it quite confusing to understand why my ANOVA
results in R were c
Any help would be most appreciated. (Don't make me get down on my
hands and knees and beg for help, cause I'll do it!!) My boss has me
learning R and doing nested regression with the report due Mon (Friday
night statistics...fun. ). Anyway, here's my problem:
In a regression equation not accounti
Hello,
This is probably a naieve question. Why does R store everything in
double-precision format? For many circumstances (e.g., dealing with
huge binary files) it seems like a waste of memory. Is there any
thought of allowing the user to decide the format when assigning an
object (e.g., as an opt
?
Thanks again for your help,
Johan Jackson
On 11/5/07, jim holtman <[EMAIL PROTECTED]> wrote:
> Even when it does start using virtual memory (which you never want it
> to do from a performance standpoint), there is still the physical
> limitation (e.g., a 2-3GB on Windows depending
Hi all,
R newbie, but have been reading the boards and learning lots. I have
read all documents & list-serve responses I could about R and memory
but still no answer.
QUESTION:
When the sizes of your objects exceeds your available RAM, R switches
to Virtual Memory right? If so, why does it so of
22 matches
Mail list logo
