if that is not specific (or not general) enough:
newDV <- dat$DV ## newDV is my DV & it is continuous.
newDV <- as.numeric(newDV)-5
str(newDV)
(i had to do a great deal of coding here so i am snipping down to the end)
tmp[which(dat$v1 == "stuff" & dat$v2 == "more stuff")] <- "lots of stuff"
tmp <- factor(tmp, levels=c("la", "la la", "fa la la"))
dat$v3 <- tmp
newIV <- as.factor(dat$v3) #### newIV is my IV, a factor as you can see.
n.var4 <- dat$v4 ## control
n.var5 <- dat$v5 ##control (there are others but they were coded the same)
n.mod1 <- lm(newDV ~ newIV + v4 + v5 + v6 + v7 + v8 + v9, data=dat) ### linear
model. all of these variables already are specific to the dataset which i
called 'norway' so there is no need to specify in the model.
summary(n.mod1)
> plot(effect("newIV", n.mod1), multiline=T)
Error in plot(effect("nor.trust", n.mod1), multiline = T) :
error in evaluating the argument 'x' in selecting a method for function
'plot': Error in apply(mod.matrix[, components], 1, prod) :
subscript out of bounds
~~this ran perfectly on my previous dataset so i am unsure of the issue.
thanks in advance.
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