Displaying 2 results from an estimated 2 matches for "mydv".
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2011 Nov 10
3
optim seems to be finding a local minimum
...rns a data frame column IV_transf:
transformIV = function(.alpha,.beta) {
IV_transf <- as.data.frame(1 - (1/exp((IV/.beta)^.alpha)))
return(IV_transf)
}
### Function "mysum" calculates the sum of absolute residuals after a
regression with a single predictor:
mysum<- function(myIV,myDV){
regr<-lm(myDV[[1]] ~ 0 + myIV[[1]])
mysum<-sum(abs(regr$resid))
return(mysum)
}
### Function to be optimized;
### param is a vector of 2 values (.alpha and .beta)
myfunc <- function(param){
myalpha<-param[1]
mybeta<-param[2]
IVtransf<-transformIV(myalpha, mybeta)...
2009 Mar 03
1
repeated measures anova, sphericity, epsilon, etc
...ated measures anova. This time around
teaching it, we are using R for all of our computations. We are starting by
covering the univariate approach to repeated measures anova.
Doing a basic repeated measures anova (univariate approach) using aov()
seems straightforward (e.g.:
+> myModel<-aov(myDV~myFactor+Error(Subjects/myFactor),data=myData)
+> summary(myModel)
Where I am currently stuck is how best to deal with the issue of the
assumption of homogeneity of treatment differences (in other words, the
sphericity assumption) - both how to test it in R and how to compute
corrected df for t...