Re: st: Power Analysis in 2-Level Hierarchical Linear Model

[William Buchanan <william@williambuchanan.net>]

Could you be more specific about what you are looking for from the power analysis? It seems that you are interested in finding the minimum detectable effect - or sensitivity analysis - from the details you've provided, but it isn't completely clear.  You could, however, always set up a simulation to test how the estimator performs using similar variances/covariances and sample size(s).  In Singer and Willett (2003) they tend to suggest using the sample size derived from level 1 units to calculate power. 

HTH,
Billy

Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York City, NY: Oxford University Press.

Sent from my iPhone

On Apr 15, 2013, at 23:04, Anthony Fulginiti <fulginitipsy@yahoo.com> wrote:

> Hello Statalist,
> 
> I have enjoyed following the creative and informative insights and guidance on Statalist over the past few months. 
> 
> I am interested in performing a power analysis in a 2-level hierarchical linear model (more specifically, a growth curve model).  
> 
> Let's use the example of 80 clusters (individuals) with 10 per cluster (observations). If it is helpful, the code for the model is: 
> 
> xtmixed Self-Esteem time time2 Program ProgramBytime ProgramBytime2|| id: time, covariance(un) variance mle
> 
> I ran a basic search in the Statalist archives and searched for power analysis options in Stata but did not find any information on the subject for hierarchical linear models. I have been reviewing material that recommends the use of Optimal Design software or PinT (Power in Two-level Designs) for power analysis in hierarchical linear modeling.  However, I have a Mac and both programs seem to run on Windows (my Windows platform has been giving me problems).  
> 
> Is it possible to perform a power analysis with a 2-level hierarchical linear model in Stata? 
> 
> If not, I would welcome any further recommendations for performing the analysis.
> 
> Thanks in advance for feedback.  
> 
> Respectfully, Anthony
> 
> 
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