Can anyone recommend a statistical software for run linear mixed models. Maybe something similar to a JMP Pro, but not as expensive for a personal usage?
For linear mixed models I'd recommend R. It is free, open source and more flexible than SPSS. The package is standard these days lme4 for most common multilevel models with additional flexibility from packages such as ordinal (for ordinal models) or brms (for Bayesian models including multilevel ones).
Just any software ( except R scripts) which can perform this operation.
For linear mixed models I'd recommend R. It is free, open source and more flexible than SPSS. The package is standard these days lme4 for most common multilevel models with additional flexibility from packages such as ordinal (for ordinal models) or brms (for Bayesian models including multilevel ones).
Hello Olga,
I recommend R for mixed models, but you can also use STATA 15, very easy to use and also that version has a module to make them under the Bayesian approach. Greetings.
In general terms you may want to look at
http://www.bristol.ac.uk/cmm/software/mlwin/mlwin-resources.html#mlmbkgrd
MLwiN is designed to be very fast and to estimate complex models:
there is a free trial version
http://www.bristol.ac.uk/cmm/software/mlwin/
I should also add that you can use MLwiN from inside Stata and R if you have it on your machine.
http://www.bristol.ac.uk/cmm/software/mlwin/mlwin-resources.html#interop
R without any doubt. There are many packages you can use. Also, there are many youtube tutorial on r packages for LMM analysis.
https://www.r-bloggers.com/linear-mixed-models-in-r/
https://www.youtube.com/watch?v=slEWKWOh990
There is a real problem (when I last looked) with the SPSS implementation of mixed models in that it does not provide a ready means of estimating the higher-level random effects - the so called shrunken residuals. For many research problems this is vital.
However, Chris Charlton has now completed the conversion of some of our online Lemma training materials into SPSS. Two Modules have been completed.
• Module 3 on using Multiple regression this can be used as a pre-cursor to the multilel part of the course
• Module 5: Introduction to Multilevel Modelling.
Importantly the latter show you how to use SPSS syntax to calculate higher- level residuals. The material separates out concepts from implementation.
You can freely use these materials to teach yourself, and/or use them in courses you are teaching.
The course already has material for MLwiN, Stata and R.
http://www.bristol.ac.uk/cmm/news/57.htmlhttp://www.bristol.ac.uk/cmm/news/57.html
http://www.bristol.ac.uk/cmm/learning/online-course/index.html
MLwiN can estimate via likelihood procedures, MCMC and iterated bootstrap.
I would also recommend R, except from lme4 check out lmerTest as well.
Just to be clear about my previous post, you can run MLwiN from within R
http://www.bristol.ac.uk/cmm/software/r2mlwin/
The reasons for doing so is the ability to fit large and complex models very rapidly, see
Zhengzheng Zhang, Richard M. A. Parker, Christopher M. J. Charlton, George Leckie, William J. Browne (2016). R2MLwiN: A Package to Run MLwiN from within R. Journal of Statistical Software, 72(10), 1-4
https://www.jstatsoft.org/article/view/v072i10
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