From: N. Brouard <brouard@ined.fr>
Date: Sun, 21 Aug 2022 09:30:43 +0000 (+0000)
Subject: *** empty log message ***
X-Git-Tag: imach-099s7~92
X-Git-Url: https://henry.ined.fr/git/?a=commitdiff_plain;h=9268ea4a8333e3df66859319790a36f35b44d146;p=.git

*** empty log message ***
---

diff --git a/src/ChangeLog b/src/ChangeLog
index a4dc81a..6f02b40 100644
--- a/src/ChangeLog
+++ b/src/ChangeLog
@@ -1,3 +1,31 @@
+2022-08-21  Nicolas Brouard   <brouard@ined.fr>
+
+	* imach.c (Module): Version 0.99r33 A lot of changes in
+	reassigning covariates: my first idea was that people will always
+	use the first covariate V1 into the model but in fact they are
+	producing data with many covariates and can use an equation model
+	with some of the covariate; it means that in a model V2+V3 instead
+	of codtabm(k,Tvaraff[j]) which calculates for combination k, for
+	three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
+	the equation model is restricted to two variables only (V2, V3)
+	and the combination for V2 should be codtabm(k,1) instead of
+	(codtabm(k,2), and the code should be
+	codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
+	made. All of these should be simplified once a day like we did in
+	hpxij() for example by using precov[nres] which is computed in
+	decoderesult for each nres of each resultline. Loop should be done
+	on the equation model globally by distinguishing only product with
+	age (which are changing with age) and no more on type of
+	covariates, single dummies, single covariates. 
+
+2022-08-06  Nicolas Brouard   <brouard@ined.fr>
+
+	*  imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
+
+2022-08-03  Nicolas Brouard   <brouard@ined.fr>
+
+	*  imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
+
 2022-07-25  Brouard Nicolas  <brouard@brouard.name>
 
 	* imach.c (Module): Error cptcovn instead of nsd in bmij (was
@@ -778,6 +806,7 @@
 
 
 =======
+>>>>>>> 1.55
 2022-07-23  Nicolas Brouard   <brouard@ined.fr>
 
 	* r29 W and not sqrt(Wald)