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<DIV><FONT face=Arial>Hello,</FONT></DIV>
<DIV> </DIV>
<DIV><FONT face=Arial>I am almost new in R, so perhaps my question will be
silly.</FONT></DIV>
<DIV><FONT face=Arial></FONT> </DIV>
<DIV><FONT face=Arial>I try to use R for analyzing capture-recapture data in
epidemiology. A cancer registry has different sources of patients. We know in
each list, patients already known in all other list. The aim is to use
capture-recapture models for estimating the number of patients unknow of all the
sources.</FONT></DIV>
<DIV><FONT face=Arial></FONT> </DIV>
<DIV><FONT face=Arial>Because no order in sources, one cannot use classical
models for closed animal populations (models M(bht) of Otis ) so I use
hierarchical loglinear model, moreover for controlling interactions (dependence)
between sources. For me it sound a little strange when I read in papers that
authors use 'glm' and 'predict' for this problem even if I know that
loglinear are in generalized linear model.</FONT></DIV>
<DIV><FONT face=Arial></FONT> </DIV>
<DIV><FONT face=Arial>Why don't use 'loglin'? What is the code for this problem
using 'glm' + 'predict'.</FONT></DIV>
<DIV> </DIV>
<DIV><FONT face=Arial>I thank you in advance for your help,</FONT></DIV>
<DIV> </DIV>
<DIV><FONT face=Arial>===================================<BR>Dr SAULEAU
Erik-A.<BR>DIM<BR>----------------------------------------------------------<BR>Etablissement
Public de Santé Alsace Nord<BR>141, Ave de Strasbourg<BR>67170 Brumath<BR>Tel :
03-88-64-61-81<BR>E-Mail: <A
href="mailto:dim.brumath@wanadoo.fr">dim.brumath@wanadoo.fr</A><BR>----------------------------------------------------------<BR>Centre
Hospitalier d'Erstein<BR>13, Route de Krafft<BR>BP F<BR>67151 Erstein
Cedex<BR>E-Mail: <A
href="mailto:dim@ch-erstein.fr">dim@ch-erstein.fr</A><BR>===================================</FONT></DIV></BODY></HTML>