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    <link>http://gmane.org</link>
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  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/130">
    <title>Gwet's AC1 Interrater reliability</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/130</link>
    <description>&lt;pre&gt;R friends,

with some help of a friend and the original author I turn available this
function which is helping me in some analysis. Perhaps it may be useful to
others... :-)

 1.
Gwet KL. Computing inter-rater reliability and its variance in the presence
of high agreement. Br J Math Stat Psychol. 2008 ;61(Pt 1):2948.

# AC1 statistic for 2 raters special case
# table = k x k table which represents table(rater1,rater2), must have
equal number of rows and columns
# N = population size which will be stick in standard error correction,
N=Inf is no correction.
# conflev = Confidence Level associated with the confidence interval (0.95
is the default value)

AC1 &amp;lt;- function(table,conflev=0.95,N=Inf,print=TRUE){
  if(dim(table)[1] != dim(table)[2]){
  stop('The table should have the same number of rows and columns!')
  }
  n &amp;lt;- sum(table)
  f &amp;lt;- n/N
  pa &amp;lt;- sum(diag(table))/n # formula 18
  q &amp;lt;- ncol(table) # number of categories
  pkk &amp;lt;- diag(table)/n
  pak &amp;lt;- sapply(1:q,function(i)sum(table[i,]))/n
  pbk &amp;lt;- sapp&lt;/pre&gt;</description>
    <dc:creator>Pedro Emmanuel Alvarenga Americano do Brasil</dc:creator>
    <dc:date>2012-05-03T17:58:17</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/127">
    <title>Cosinor Model (Halberg,Bingham) - Multiple components - Linear, Quadratic and Cubic trends</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/127</link>
    <description>&lt;pre&gt;

Hello!

I have a doubt in relation with the use of the cosinor model with R when I have not only multiple components, but also linear, quadratic and cubic trends.

I explain the details:

In simple cosinor:


Y = M + A * cos(2
* Ï* t / T + Ï) + error

T knowed: y = M + Î²* X1 + Ï* X2 + error,
Â 
Where X1 = cos (2 * Ï* t / T) and X2 = sin(2
* Ï* t / T)
Â 
In this
case, I use lm(y ~ X1 + X2) .
Â 
For the
multiple components case:
Â 
y = M + âAj * cos(2 * Ï * t /Tj + Ïj) + error
Â 
In this
case I use:Â  lm(y ~ X1tot + X2tot)
Â 
However, in
the generalized model case (linear, quadratic and cubic trends), I donât know
how to analyze with R.
Â 
I include
the situacion formula:
Â 
y = M + Î±1 * t + Î±2 * t2 + Î±3 * t3+ âAj *
cos(2 *Ï* t /Tj + Ï2) + error
Â 
What
function in R can I use, as I used lm for the simple cosinor model and the
multiple components model?.
Â 
How can I
obtain global information and separated information?. I refer to ob&lt;/pre&gt;</description>
    <dc:creator>Iva P</dc:creator>
    <dc:date>2012-03-18T10:21:11</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/123">
    <title>Linear excess relative risk modelling in R</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/123</link>
    <description>&lt;pre&gt;Dear List,



I am attempting to carry out linear excess relative risk modelling for the
purposes of a nested case-control study of nuclear industry workers.



The majority of similar analyses in the literature have been carried out
using EPICURE, SAS or STATA, or have been implemented directly in FORTRAN.
For a number of reasons, it would be preferable for me to carry out the
analysis in R, but I am having difficulty finding an appropriate R
package.



Many thanks in advance for any advice on this matter,



James Grellier



James Grellier PhD

CREAL-Centre for Research in Environmental Epidemiology
Parc de Recerca Biomèdica de Barcelona (despatx 183.01.A)
Doctor Aiguader, 88 | 08003 Barcelona



Tel. +34 932 147 345
jgrellier-MstSlu9blcReoWH0uzbU5w&amp;lt; at &amp;gt;public.gmane.org

 &amp;lt;http://www.creal.cat/&amp;gt; www.creal.cat




[[alternative HTML version deleted]]

&lt;/pre&gt;</description>
    <dc:creator>Grellier, James</dc:creator>
    <dc:date>2012-01-11T13:08:55</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/122">
    <title>Course: Age-Period-Cohort models, Lisbon, September 2011</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/122</link>
    <description>&lt;pre&gt;Course on Age-Period-Cohort models.
===================================
   Place: Lisbon
    Time: Monday 19th - Wednesday 21st September 2011. 
Deadline: 1 September 2011
     Fee: 380 EUR.
 Teacher: Bendix Carstensen, Steno Diabetes Center, Copenhagen
     URL: http://www.ceaul.fc.ul.pt/seeevent.html?id=206
          http://staff.pubhealth.ku.dk/~bxc/APC/Lisboa-2011
          ( The latter contains links to various material on the topic )
Audience: Epidemiologists and Statisticians.

Age-Period-Cohort models for mortality and morbidity rates is a useful tool for description of age- and time-trends. But the use and in particular the reporting is not straightforward.

The course will cover both the basics of tabulation of data, modeling and choice of parametrization as well as the more advanced aspects of Age-Period-Cohort models, including a substantial practical component, based on computer exercises in R. Specifically the apc-tools in the Epi package for R will be covered in some depth.

Formally no prereq&lt;/pre&gt;</description>
    <dc:creator>BXC (Bendix Carstensen</dc:creator>
    <dc:date>2011-07-23T12:07:31</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/121">
    <title>Running R on a Computer Cluster in the Cloud -cloudnumbers.com</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/121</link>
    <description>&lt;pre&gt;Dear epidemiological data analysis and R experts,

cloudnumbers.com provides researchers and companies with the resources
to perform high performance calculations in the cloud. As
cloudnumbers.com's community manager I may invite you to register and
test R on a computer cluster in the cloud for free:
http://my.cloudnumbers.com/register

Our aim is to change the way of research collaboration is done today by
bringing together scientists and businesses from all over the world on a
single platform. cloudnumbers.com is a Berlin (Germany) based
international high-tech startup striving for enabling everyone to
benefit from the High Performance Computing related advantages of the
cloud. We provide easy access to applications running on any kind of
computer hardware: from single core high memory machines up to 1000
cores computer clusters.

Our platform provides several advantages:

* Turn fixed into variable costs and pay only for the capacity you need.
Watch our latest saving costs with cloudnumbers.com video:
htt&lt;/pre&gt;</description>
    <dc:creator>Markus Schmidberger</dc:creator>
    <dc:date>2011-07-07T18:11:25</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/120">
    <title>Course: Statistical Practice in Epidemiology with R</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/120</link>
    <description>&lt;pre&gt;Many of the subscribers to R-SIG-Epi will be familiar with the course
Statistical Practice in Epidemiology with R, which normally takes place
in Tartu, Estonia.  This year, the course will take place in Lyon,
France 5-9 September. 

The course is intended for epidemiologists and statisticians who wish to
use R  for statistical modelling and analysis of epidemiological data.
The aim of the course is to give participants access to a set of tools
in current use by statisticians in epidemiology. The course requires
fairly good understanding of statistical principles and some familiarity
with epidemiological concepts and study types.

The course is mainly practically oriented with more than half the 
time at the computer.

For more information see 
http://www.iarc.fr/en/education-training/R/
http://www.pubhealth.ku.dk/~BXC/SPE/

To apply for the course, download and fill in the application form. The
deadline for applications is 21 May.



-----------------------------------------------------------------------
Thi&lt;/pre&gt;</description>
    <dc:creator>Martyn Plummer</dc:creator>
    <dc:date>2011-04-26T13:48:04</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/119">
    <title>OR in HGLM</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/119</link>
    <description>&lt;pre&gt;Dear All,

I  was  wondering how I can  generate adjusted odds  ratio confidence intervals  using the hglm package? I  know you can simply  use the exponential of the estimate to get the OR,  but I  am not sure how you  can get the  equivalent of the " logistic.display"  in epicalc that will also  generate the  CI's.  I  know this is   very  elementary  question.

Russell " Skip" Barbour  Ph.D.
Yale School  of Medicine
135 College St.  Suit 200
New Haven ,  CT. 06510
Tel: 203 764 4332
Fax: 203 764 4353
Email: russell.barbour-LrD5EImo2rg&amp;lt; at &amp;gt;public.gmane.org&amp;lt;mailto:russell.barbour-LrD5EImo2rg&amp;lt; at &amp;gt;public.gmane.org&amp;gt;


Doubt grows with knowledge.
Johann Wolfgang von Goethe&amp;lt;http://www.brainyquote.com/quotes/quotes/j/johannwolf380192.html&amp;gt;



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&lt;/pre&gt;</description>
    <dc:creator>Barbour, Russell</dc:creator>
    <dc:date>2011-03-30T21:37:18</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/110">
    <title>converting string to a object name of a dataset</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/110</link>
    <description>&lt;pre&gt;Hi,

I am trying to access object which is variable of a dataset using
string.  For that I am trying to convert a string to the object name
in the following code. But unfortunately it looks something is going
wrong in the following code.

data1&amp;lt;- data.frame(x=c(1:4), y=rep(1:4))
gvars&amp;lt;- c("x", "y")
z&amp;lt;- paste("data1", gvars[1], sep="$")
get(z)

The above code should return following output:
[1] 1 2 3 4

but instead it is printing following error
"Error in get(z) : object 'data1$x' not found"

Please help me to fix the problem.

Regards
Madan

&lt;/pre&gt;</description>
    <dc:creator>Madan Gopal Kundu</dc:creator>
    <dc:date>2011-03-18T05:18:55</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/108">
    <title>Compare calibration from two LR models</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/108</link>
    <description>&lt;pre&gt;Dear Friends,
 
I have the following question on comparing calibration (using Hosmer-Lemeshow test) of two logistic regression models based on reported p-value.
 
Can we use p-values for comparing calibration for two different logistic regression models? If one model has p value .2 and another model has .8, is it justified to conclude that second model is better calibrated compare to the first model ? [My intuition says NO, because p- value only measure of consistency between the observed data and the null hypothesis. And, here the null hypothesis is that the model is well calibrated. p-value does not tell about how strong the calibration is.]
 
Thank you for your response.
 
Best regards,
Suman Kundu
PhD student.
Erasmus MC, Rotterdam
 


      
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&lt;/pre&gt;</description>
    <dc:creator>Suman Kundu</dc:creator>
    <dc:date>2011-02-16T14:54:26</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/105">
    <title>Calculate local RR from GAM</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/105</link>
    <description>&lt;pre&gt;Dear Group,
I am just a beginner in Epidemiology, epi-statistics and this group hence, in advance
I apologize if I ask trivial question.

I would like to ask how is it possible to calculate from GAM (general
additive model) Relative Risk
the model has following formula:
log(E[O_i]) ~ log(N_i) + someCovariates_i, where Oi is number of cases
of some disease in i-th area, N is population at risk in i-th area,
other covariates are i-th region specific.
I one paper authors calculated RR for each i-th region out of this model, but I have no
idea how can I do it myself.



Kindest regards,

pj

&lt;/pre&gt;</description>
    <dc:creator>Przemysław Jura</dc:creator>
    <dc:date>2011-02-09T13:37:45</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/102">
    <title>LD between diallelic and multiallelic loci</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/102</link>
    <description>&lt;pre&gt;Dear all,

I am planning to analyse linkage between two loci( first - diallelic, 
second - multiallelic (HLA-DRB1)). What function should i use?
Usually I use LD(data) function but it doesn't work if number of locus' 
alleles more then 2.

Thanks for your time.

Best wishes,
Ekaterina Kudryavtseva
PhD student,
Department of Molecular Biology
Novosibirsk University
Tel: +7-923-185-82-47







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&lt;/pre&gt;</description>
    <dc:creator>Екатерина Кудрявцева</dc:creator>
    <dc:date>2011-01-25T13:13:44</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/100">
    <title>cox model with time-dependent covariates</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/100</link>
    <description>&lt;pre&gt;Dear all,

I am planning to run a cox model with time-dependent covariates. I would
like to use the 'fold' function (Fox, 2002:
http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-cox-regression.pdf)
to create the dataset, with one observation per subject &amp;amp; time-window, and
then  use the 'coxph' function of the survival package to run the model.

However, I had a couple of questions, and I can't find the answer on the
internet:

1. In the document writtent by Fox, the new dataset created for the
purpose of the time-dependent covariates model (Rossi.2) numbers the
observations 1.1, 1.2, 1.3, 1.4, 1.5, etc. which corresponds to the
measurements in the different time-windows for subject 1. My question is
the following: if I run a cox model on such a dataset, is the model
accounting for the fact that 1.1, 1.2, 1.3, ... belongs to the same
subject?

2. I will have a big dataset, i.e. 40,000 subjects and 36 time-windows,
i.e. 1,440,000 lines, and about 20 covariates. I was wondering if I should
expect som&lt;/pre&gt;</description>
    <dc:creator>raphaëlle métras</dc:creator>
    <dc:date>2011-01-17T12:22:47</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/99">
    <title>Risk Ratio tables</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/99</link>
    <description>&lt;pre&gt;Hello R friends,

This last year I became awere of some modern strategies of varible selection
for regression analisys, such as bootstrap, bayesian approaches and others.
Nevertheless, most analysts (that Im awere of) find it usefull to compare
crude measures with adjusted ones to have an idea of direction and magnitude
of confounding. In a recent report, I had some work to make a table with
several crude risk ratios, then I made a function to invoke riskratio
function and display the riskratio of several exposures for the same
outcome. It was inspired in epicalc::tableStack. Unfortunately, I could not
avoid the many for(), but I guess it would not be much a problem with small
datasets. It assumes that both the exposures and the outcome are binary
variables. But I guess that with little improvementes could work with more
categories too. Similar to tableStack, its output may be easily be exported
to a spreadsheet with write.table or other export function.

I hope it is usefull to others too.

rrStack &amp;lt;- funct&lt;/pre&gt;</description>
    <dc:creator>Pedro Emmanuel Alvarenga Americano do Brasil</dc:creator>
    <dc:date>2011-01-08T02:55:04</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/96">
    <title>Frequencies like Epiinfo</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/96</link>
    <description>&lt;pre&gt; 

I am trying to make a function that works like the command Frequencies of
Epiinfo. I am a beginner user and I make something like this:

 

freq&amp;lt;-function(x){

Frecuencia&amp;lt;-table(x,exclude=NULL);

Porcentaje&amp;lt;-as.vector(round(prop.table(table(x,exclude=NULL)),2));

Porc&amp;lt;-as.vector(round(prop.table(table(x,exclude=NULL))*100,1));

Acumulado&amp;lt;-cumsum(Porc);

IC95.Sup&amp;lt;-round(as.vector(Porc+196*sqrt(Porcentaje*(1-Porcentaje)/sum(Frecue
ncia))),1);

IC95.Inf&amp;lt;-round(as.vector(Porc-196*sqrt(Porcentaje*(1-Porcentaje)/sum(Frecue
ncia))),1);

matrix(

c(Frecuencia,sum(Frecuencia),Porc,round(sum(Porc),1),

Acumulado,NA,IC95.Inf,NA,IC95.Sup,NA),length(Frecuencia)+1,5,

dimnames=list(c(labels(Frecuencia)[[1]],"Total"),c("Frecuencia","Porcentaje"
,"Acumulado","[IC--","--95%]"))

);

}

 

There is a way more efficient to create a function like this?

there is a way to make it more visually - friendly adding something like
-------------- that stat.table does?

How can I add an argument like missing=T that show NA's and mis&lt;/pre&gt;</description>
    <dc:creator>Diego Garcilazo</dc:creator>
    <dc:date>2010-11-29T21:36:21</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/93">
    <title>help</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/93</link>
    <description>&lt;pre&gt;Sir,

Its wonderful to start using this software R. I am making full efforts to
learn it on my own with the help of the free online manuals available. I am
using epicalc package in R. I have a dataset where i want to apply
conditions like... if var1 is yes or 1, assign 1 to it or else 0. Can you
help me with this problem?

Thanking you,

&lt;/pre&gt;</description>
    <dc:creator>Dr Khan Amir Maroof</dc:creator>
    <dc:date>2010-11-27T05:30:44</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/90">
    <title>Reference group in logistic regression analysis</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/90</link>
    <description>&lt;pre&gt;To someone who could help me:

I am a PhD student, working in the Novosibirsk University, Russia. I
am now using glm() function to do logistic regression analysis.
I cannot understand how the chosen reference group. For example, for the
three genotypes of GG, GC, CC I want to be risk assessed in relation to
the genotype CC, but the program selects the genotype GG. How do I
change the reference group?


Thanks for your time.
Best wishes,
Ekaterina Kudryavtseva
PhD student,
Department of Molecular Biology
Novosibirsk University
Tel: +7-923-185-82-47

&lt;/pre&gt;</description>
    <dc:creator>Екатерина Кудрявцева</dc:creator>
    <dc:date>2010-10-28T07:56:53</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/88">
    <title>Kindly help me of applicability of PLSR method forbinary outcome variable</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/88</link>
    <description>&lt;pre&gt;Dear friends, 

I am a PhD student at Erasmus Medical Centre, Rotterdam, The Netherlands. I found the R package "pls", which is very handy and useful. This package descibes how to use Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR).
Would you mind to kindly answer the following? 
Logistic regression (LR) is a commonly used method in medical science to make a prediction model for binary outcome variable. This is fine, and I would like to apply (if applicable) PLSR and PCR to construct a prediction model for binary outcome variable, and will check whether PLSR or PCR method helps to make better model compare to LR method, in the sence of discrimination and goodness-of-fit (calibration). However, I am not sure whether the R package "pls" allows to construct such a model. 
I will be pleased if you kindly let me know whether PLSR ( or PCR) method is applicable for binary outcome variable. 

Thank you very much for your suggestions. 

Kind regards, 
Suman Kundu 



[[alternativ&lt;/pre&gt;</description>
    <dc:creator>Suman Kundu</dc:creator>
    <dc:date>2010-10-27T08:48:52</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/87">
    <title>Competing risks with time-varying covariates</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/87</link>
    <description>&lt;pre&gt;Dear list,

This is a somewhat off-topic question as I don't have a specific issue
with an R-function, but rather seek advice on how to proceed with my
analyses.

I have survival data on approximately 2000 subjects followed for about
35 years. The subjects had their first medical examination at the age
of 50 and were examined almost every 10th year after that, so the data
is in long form with multiple records per subject.

The event of interest now is cardiovascular mortality with mortality
from other causes being a competing event. I consider myself a novice
when it comes to analysis of these kinds of data, so as far as I
understand estimating the survival function is not of much use as I
have time-varying covariates. I therefore turned my attention to the
Poisson representation of the Cox model. I have created a dataset with
yearly increments of time (with age as the time-scale) using the Lexis
and splitLexis functions in the Epi package v. 1.1.17. Additionaly the
dataset has been duplicated and the status&lt;/pre&gt;</description>
    <dc:creator>Erik Lampa</dc:creator>
    <dc:date>2010-10-13T09:10:46</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/86">
    <title>mvtnorm -- rates of occurence</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/86</link>
    <description>&lt;pre&gt;We're trying to identify articles where investigators have used mvtnorm to estimate rates of occurrence of a condition or rates of eligibility for services.  In our application we used  a pentavariate normal cumulative distribution function to determine how many children are likely be eligible for disability services because they fall -2 SD on any of 5 developmental domains.

Thanks

Steve

Steven Rosenberg, Ph.D.
Associate Professor
Department of Psychiatry
University of Colorado Denver
Campus Box C268-22
4455 E. 12th Avenue
Denver CO 80220
303-315-9121


[[alternative HTML version deleted]]

&lt;/pre&gt;</description>
    <dc:creator>Rosenberg, Steven</dc:creator>
    <dc:date>2010-10-08T18:21:18</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/82">
    <title>R and Epi Info</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/82</link>
    <description>&lt;pre&gt;Hello,



   I was wondering who to contact to see about somehow interconnecting or integrating the programs R and Epi Info.  I have been involved in the development of Epi Info which is a software program developed by CDC (www.cdc.gov/epiinfo&amp;lt;http://www.cdc.gov/epiinfo&amp;gt;).  Epi Info allows for creating data entry systems and performs certain epidemiologic and statistical analyses.  Currently Epi Info is in the public domain and I believe future versions will be open source.  It might be useful to pull together some of the Epi Info development team members and R team members to discuss how the programs might complement each other.  Note that I send this e-mail as an effort to combine the efforts of these two groups and this is not an official request from CDC.

  Thanks, Kevin

Kevin M. Sullivan, PhD, MPH, MHA
Associate Professor
Department of Epidemiology
Rollins School of Public Health at Emory Univerisity
Claudia Nance Rollins Building (CNR), Room 3051
1518 Clifton Road, NE
Atlanta, GA 30322
USA

Office Ph&lt;/pre&gt;</description>
    <dc:creator>Sullivan, Kevin M</dc:creator>
    <dc:date>2010-09-01T19:08:21</dc:date>
  </item>
  <item rdf:about="http://comments.gmane.org/gmane.comp.lang.r.epi/78">
    <title>random-effects modeling</title>
    <link>http://comments.gmane.org/gmane.comp.lang.r.epi/78</link>
    <description>&lt;pre&gt;Hi all,



Being new to analysing epidemiologic data, I have a question about the following data set:

A friend has inspected three randomly chosen farms (random factor 'farm'). At each farm three randomly chosen series of chickens (random factor 'flock') were each inspected for the presence of a certain bacteria. The contaminated chickens were counted (response variable 'positives'). The sample sizes per flock are given by 'broilers'. We want to have a look at within-broilers, within-farm and between-farm variability.



It seems to me that we have a random-effects model, in which the factor 'flock' is nested within the factor 'farm'. Am I correct so far?

Now, since the response variable yields count data, fitting the model should be done using Poisson regression. Correct?



Could somebody help me out with (an example of) such an analysis?



Many thanks in advance,

Dieter



Here is the dataset used:



broilers&amp;lt;-data.frame(farm=c("FA","FA","FA","FB","FB","FB","FC","FC","FC"), flock=c("a","b","c","d","e&lt;/pre&gt;</description>
    <dc:creator>dieter.anseeuw</dc:creator>
    <dc:date>2010-08-17T05:28:47</dc:date>
  </item>
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