search for: lowb

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2008 Apr 22
3
Using the 'by' function within a 'for' loop
...9;, omi=c(0.8,0.25,1.2,0.15), mai=c(1.1,0.8,0.3,0.3)) for (k in variable) { dat<-dato[!is.na(k),] summ<-by(dat,dat[,c("tx","day")], function(x) { mn<-mean(x$k) std<-sd(x$k) n<-length(x$k) se<-std/sqrt(n) lowb<-mn-se upb<-mn+se data.frame(tx=x$tx[1],day=x$day[1],mn=mn,std=std,lowb=lowb,upb=upb,se=se) }) summ<-do.call("rbind",summ) #Definining x axis range xmax<-unique(max(summ$day,na.rm=TRUE)) xmin<-unique(min(summ$day,na.rm=TRUE)...
2008 Apr 21
0
Using the 'by' function withing a 'for' loop
...9;, omi=c(0.8,0.25,1.2,0.15), mai=c(1.1,0.8,0.3,0.3)) for (k in variable) { dat<-dato[!is.na(k),] summ<-by(dat,dat[,c("tx","day")], function(x) { mn<-mean(x$k) std<-sd(x$k) n<-length(x$k) se<-std/sqrt(n) lowb<-mn-se upb<-mn+se data.frame(tx=x$tx[1],day=x$day[1],mn=mn,std=std,lowb=lowb,upb=upb,se=se) }) summ<-do.call("rbind",summ) #Definining x axis range xmax<-unique(max(summ$day,na.rm=TRUE)) xmin<-unique(min(summ$day,na.rm=TRUE)...
2010 Apr 05
3
bootstrap confidence intervals, non iid
hello, i need to calculate ci's for each of 4 groups within a dataset, to be able to infere about differences in the variable "similarity". the problem is that data within groups is dependent, as assigned by the blocking-factor "site". my guess was to use a block bootstrap but samples within in these blocks / sites are not of same length. i was not able to find a method to