[R] Standard deviation from MANOVA??

[BrutishFruit]

Thanks for all help so far!
And I seems as you are correct Peter (and Jean too).
And I have now investigated and found how it is connected with the standard
errors:

If use the following code (taking from Jeans example code), where we have
one manova and two individual models (continue read comments in code):

# ------- code starts -------- #
mydata <- data.frame(y1=rnorm(50), y2=rnorm(50), x1=rnorm(50), 
x2=rnorm(50), x3=rnorm(50)) 
 
myfit <- manova(cbind(y1, y2) ~ x1 + x2 + x3, data=mydata) 

myfit1 <- lm(y1 ~ x1 + x2 + x3, data=mydata) 
myfit2 <- lm(y2 ~ x1 + x2 + x3, data=mydata)

# And then gets the standard error for each of the three models:

stderr <- predict.lm(myfit, type="response", se.fit=TRUE)[[2]]
stderr1 <- predict.lm(myfit1, type="response", se.fit=TRUE)[[2]]
stderr2 <- predict.lm(myfit2, type="response", se.fit=TRUE)[[2]]

# Will we get that stderr = sqrt(stderr1^2+stderr2^2)

print(cbind(stderr,sqrt(stderr1^2 + stderr2^2)))

# ------- code ends -------- #

So, the reason why the output only gave one standard error when I was
writing:

“But if I type:     predict.lm(myfit, type="response", se.fit=TRUE) 
I get the predicted values and standard deviation, but only for y1 (and
nothing from y2...). “

was because the output gave the combined error for both y1 and y2 by using
the following formula:
sqrt(stderr1^2 + stderr2^2). So it wasn't standard error for just y1 as I
thought.

You can test the provided code above and see that relationship is as
described.

So then my problem is solved as I can get the individual standard error for
y1 and y2. Even if I don’t understand how you could/should use the combined
standard error you get from the manova model (myfit)…

//BF
Mattias Siljestam
Uppsala University



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