search for: chisqtest

I have a dataset called "raw-data" . I am trying to use the following code - col_name<-names(raw_data) for (i in 1:(length(names(raw_data))-2)) { tbl=table(raw_data$Pay.Late.Dummy, raw_data$col_name[i]) chisqtest<-chisq.test(tbl) } Say the 1st column of my raw_data is Column1. The idea is when i=1 then raw_data$col_name[i] will automatically become raw_data$Column1 , which is not happening. Kindly help? -- View this message in context: http://r.789695.n4.nabble.com/Replace-a-variable-by-its-value-tp46...

...t, but I think Peter is with me when I say that this is not the right thing in an intro course.) * Should we extend print.htest() to display info on expected and observed counts in case it is there? * (Should we have an extra argument to control this behavior?) * Or should there be a class "chisqtest" with a slightly different print and perhaps also summary method? * Or ...? -k =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]sub...

...use thats what I'm teaching at present. I have an "lm.predict" about ready to roll, but am a bit hung up on trying to propagate case names through "model.frame", which in turn is inducing an sidetrack into [<- etc etc ... alternatively, you would make a new class 'chisqtest' but give your test results BOTH classes class(res) <- c("chisqtest","htest") Such that you can use 'htest' methods in general, and just one print.chisqtest in particular. I'd probably try to avoid making a separate class for every kind of test resul...

...lt;-2*(type=='m')+4*(type=='t')+rnorm(240,100,20) dat<-cbind(as.data.frame(y),type=type,batch=batch) rm(batch,type,y) library(nlme) dat.lme<-lme(y~type, random=~1|batch/type, data=dat) library(multcomp) summary(glht(dat.lme, linfct = mcp(type =c("b+t-2*m=0"))),test=Chisqtest()) library(contrast) contrast(dat.lme, a=list(type=c('b','t')), b=list(type='m'),type='average') Does anybody have a clue? Thanks, John ____________________________________________________________________________________ Never miss a thing. M...

...9992574 0.0003999703 r.worker Intercept 0.0199992574 0.0003999703 to see if removal is overall dependend upon treatment i use the package multcomp as following with the second warning message: pp.coxme.glht<-glht(pp.coxme,linfct=mcp(treatment="Tukey")) summary(pp.coxme.glht,test=Chisqtest()) General Linear Hypotheses Multiple Comparisons of Means: Tukey Contrasts Linear Hypotheses: Estimate tx - meta == 0 -22.1626 uv - meta == 0 -0.6932 uv - tx == 0 21.4694 Global Test: Chisq DF Pr(>Chisq) 1 71.94 1 2.217e-17 Warning message: In cov2cor(cov...