Displaying 4 results from an estimated 4 matches for "ses2".
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res2
2013 May 01
2
Factors and Multinomial Logistic Regression
...ds
Lorenzo
###########################################################################
library(ares)
library(foreign)
## See the Stata example at http://bit.ly/11VG4ha
mydata <- read.dta("http://www.ats.ucla.edu/stat/data/hsb2.dta")
## IMPORTANT: redefine the base line!!!
mydata$ses2 <- relevel(mydata$ses, ref = "middle")
mymodel <- multinom(ses2 ~ science+ socst+ female, data=mydata)
print(summary(mymodel))
print("The relative risk ratio (RRR) is, ")
print(exp(coef(mymodel)))
2009 Apr 16
2
error bars in matplot
...t(mat1,pch=c('x','o'),type = "b",lwd = 2,lty = c(1,2),
col = c("green","black"),cex.main = 1.8,cex=2,cex.lab=1.5,
main = "Graph 1",xlab = "Numbers 1",ylab = "Numbers 2",cex.axis = 1.6,axes=F)
plotCI(rep(vect,2),mat1,ses2,pch=NA,add=T,
col=rep(c("green","black"),each=nrow(mat1)))
axis(1,1:5,labels = vect,cex.axis=1.5)
axis(2,cex.axis=1.5)
#------------------
I don't get the error bars though. If I set 'add = F' in plotCI function, then I can see the error bars, but they ju...
2008 Jul 25
0
resynv onnv-gate
..._softtoken/common/softDecryptUtil.c
usr/src/lib/pkcs11/pkcs11_softtoken/common/softEncryptUtil.c
usr/src/lib/pkcs11/pkcs11_softtoken/common/softKeysUtil.c
usr/src/lib/pkcs11/pkcs11_softtoken/common/softSlotToken.c
usr/src/lib/print/libpapi-common/common/attribute.c
usr/src/lib/scsi/plugins/ses/ses2/common/ses2.h
usr/src/lib/scsi/plugins/ses/ses2/common/ses2_element.c
usr/src/pkgdefs/SUNWfmd/prototype_sparc
usr/src/pkgdefs/SUNWfsu/prototype_cc_sparc
usr/src/pkgdefs/SUNWfsu/prototype_gcc_sparc
usr/src/pkgdefs/SUNWnge/postinstall
usr/src/tools/ndrgen/ndrgen.sh
usr/src/tools/scripts/wx2hg....
2009 Jul 16
0
how to get means and confidence limits after glmmPQL or lmer
...he lmer
model (dlm):
ses<-predict(mm,
data.frame(treatment=c('b1','b10','b20')),type="response", se.fit=TRUE)
Error in predict.lme(object, newdata, level = level, na.action = na.action) :
Cannot evaluate groups for desired levels on "newdata"
ses2<-predict(dlm,
data.frame(treatment=c('b1','b10','b20')),type="response", se.fit=TRUE)
Error in UseMethod("predict") : no applicable method for "predict"
Any advice on how to get the means and CIs on the original scale
after fitting my si...