[RESOLVED] lm(), manova(), mancova() - what's the differenc?
Posted: Tue Dec 12, 2017 10:06 am
Hello,
I'm wondering what the difference is between a few functions in R:
manova(outcome ~ predictor+predictor)
lm(outcome ~ predictor+predictor)
then your package
mancova(data, deps, factors = NULL, covs = NULL, multivar = list("pillai",
"wilks", "hotel", "roy"), boxM = FALSE, shapiro = FALSE, qqPlot = FALSE)
I Googled - how to do a MANCOVA In R
and there was one answer:
manova(outcome ~ predictor+predictor)
Your package does not even use the ~ operator.
But is it doing the same thing behind the scenes?
It seems the llm amd manova functions somehow use the cumulative sum (using +) of variables
- whereas your package does not do this same thing? - it operationalises the variables using a comma ,
Does this make a difference?
I noticed that the Mulitple Regression (lm function) only gives me the output comparable to your 'Univariate' output. And there are differences in terms of which variables are significant for which latents compared to the mancova function.
Are these not using the same Least Square estimator?
Why would the results be different?
Many thanks for your time in helping me to understand all of this.
I'm wondering what the difference is between a few functions in R:
manova(outcome ~ predictor+predictor)
lm(outcome ~ predictor+predictor)
then your package
mancova(data, deps, factors = NULL, covs = NULL, multivar = list("pillai",
"wilks", "hotel", "roy"), boxM = FALSE, shapiro = FALSE, qqPlot = FALSE)
I Googled - how to do a MANCOVA In R
and there was one answer:
manova(outcome ~ predictor+predictor)
Your package does not even use the ~ operator.
But is it doing the same thing behind the scenes?
It seems the llm amd manova functions somehow use the cumulative sum (using +) of variables
- whereas your package does not do this same thing? - it operationalises the variables using a comma ,
Does this make a difference?
I noticed that the Mulitple Regression (lm function) only gives me the output comparable to your 'Univariate' output. And there are differences in terms of which variables are significant for which latents compared to the mancova function.
Are these not using the same Least Square estimator?
Why would the results be different?
Many thanks for your time in helping me to understand all of this.