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2017 Dec 28
1
Why aov() with Error() gives three strata?
...strata. Is it possible to have two or three strata depending on the data? If there is always three strata, how this would fit the interpretation of between vs within effects? Below a reproducible example that gives three strata: data(beavers) data=data.frame(id = rep(c("beaver1","beaver2"),c(nrow(beaver1),nrow(beaver2))),rbind(beaver1,beaver2)) data$activ=factor(data$activ) #balance dataset to have 6 samples for every combination of beaver and activity. balanced = split(data,interaction(data$id,data$activ)) sizes = sapply(balanced,nrow) selected = lapply(sizes,sample.int,6) ba...
2017 Dec 28
1
Why aov() with Error() gives three strata?
...r three strata depending on the data? > If there is always three strata, how this would fit the interpretation of > between vs within effects? > > Below a reproducible example that gives three strata: > > data(beavers) > data=data.frame(id = > rep(c("beaver1","beaver2"),c(nrow(beaver1),nrow(beaver2))),rbind(beaver1,beaver2)) > data$activ=factor(data$activ) > #balance dataset to have 6 samples for every combination of beaver and > activity. > balanced = split(data,interaction(data$id,data$activ)) > sizes = sapply(balanced,nrow) > selected =...
2017 Dec 28
1
Why aov() with Error() gives three strata?
...t; > If there is always three strata, how this would fit the interpretation of > > between vs within effects? > > > > Below a reproducible example that gives three strata: > > > > data(beavers) > > data=data.frame(id = > > rep(c("beaver1","beaver2"),c(nrow(beaver1),nrow(beaver2))), > rbind(beaver1,beaver2)) > > data$activ=factor(data$activ) > > #balance dataset to have 6 samples for every combination of beaver and > > activity. > > balanced = split(data,interaction(data$id,data$activ)) > > sizes = sapply...
2017 Dec 29
1
Why aov() with Error() gives three strata?
...ays three strata, how this would fit the interpretation of >>> between vs within effects? >>> >>> Below a reproducible example that gives three strata: >>> >>> data(beavers) >>> data=data.frame(id = >>> rep(c("beaver1","beaver2"),c(nrow(beaver1),nrow(beaver2))), >> rbind(beaver1,beaver2)) >>> data$activ=factor(data$activ) >>> #balance dataset to have 6 samples for every combination of beaver and >>> activity. >>> balanced = split(data,interaction(data$id,data$activ)) >>...