Is it possible to apply Multilevel models when data set consists of 3 IVs of categorical nature and 1 or more continuous DVs ?.......... My data set consists of 3 categorical IVs (1st IV consists of 2 categories, Second IV also consists of 2 Categories and 3rd IV consists of 3 categories).
I think yes, if they are dependent to each other, then MLM (3-level) is the best. check the answer starts 1:38:39. If IVs are independent, then do several ANOVA tests or Multivariate. ** I am new in statistics, so please let me know if you got an answer!
So (see~58mins) the beta-zero-j term is the group mean that with the r-i-j term predicts the outcome value for the ith individual in the jth group [level 1 level of analysis], and, the gamma-zero-zero term is the the mean of all group level (level 2) means that with the mu-zero-j term gives the outcome value for the jth group [level 2 level of analysis]?
17:54 "Statistical independence is more of a covariance. This is by definition." Independence of a collection of random variables implies that the covariances among them will be zero, but a covariance of zero does not imply independence. So not only is one not explicitly defined in terms of the other, but they're not equivalent either. en.wikipedia.org/wiki/Independence_(probability_theory)
Thank you Professor.
My fav lecturer ever
at 44:00 it's the other way around round? The first three ones are negative and the last three are positive
Yes, i stumbled across this, too.
Thank you very much! Very helpful :)
Is it possible to apply Multilevel models when data set consists of 3 IVs of categorical nature and 1 or more continuous DVs ?..........
My data set consists of 3 categorical IVs (1st IV consists of 2 categories, Second IV also consists of 2 Categories and 3rd IV consists of 3 categories).
I think yes, if they are dependent to each other, then MLM (3-level) is the best. check the answer starts 1:38:39. If IVs are independent, then do several ANOVA tests or Multivariate. ** I am new in statistics, so please let me know if you got an answer!
Really enjoyed this lecture!
great lecture, thanks a lot!
So (see~58mins) the beta-zero-j term is the group mean that with the r-i-j term predicts the outcome value for the ith individual in the jth group [level 1 level of analysis], and, the gamma-zero-zero term is the the mean of all group level (level 2) means that with the mu-zero-j term gives the outcome value for the jth group [level 2 level of analysis]?
17:54 "Statistical independence is more of a covariance. This is by definition."
Independence of a collection of random variables implies that the covariances among them will be zero, but a covariance of zero does not imply independence. So not only is one not explicitly defined in terms of the other, but they're not equivalent either.
en.wikipedia.org/wiki/Independence_(probability_theory)
'Hi, I'm John Nezlek. I'm not stupid and I never make mistakes.'
1:30:44 The Only way For Any Thing To Be Seamless
clear explanation, thank you!
32:00 On Aggregated Means
Does anyone by any chance have the references on power of multilevel modeling that he is referring to?
Very informative, thank you
Wonderful!
The discussion of fixed effect is very misleading. No software uses LSDV to estimate fixed effect. They use demean or first difference instead.
Can i get this presentation?
Clear explanations
58:00 Begin With Unconditional No Predictor Vari
Really gr8
Thank you. Subtitles would be a bounce.
Slides please
31:08
i wish it was using r programming
Good