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My Research   BAUW   BMEM   Consulting & Collaboration   Dynamic Models   MedCI   R   SAS GCM power   SAS WinBUGS   WebStatR   Publications   Programs   In Progress   Favorites Web This Site   Contents   >Using R and Mplus for growth curve power analysis based on likelihood ratio test >SAS WinBUGS using multiple chains >Download BMEM Binaries for PC, Mac, and Ubuntu can be downloaded. >Using OpenBUGS with SAS To use OpenBUGS with SAS, one needs to change a few things in the SAS WinBUGS codes including: (1) change the batch commands for OpenBUGS (2) change the SAS macros (3) download the customized OpenBUGS >Some selected software/programs for power analysis of growth curve models and multilevel models Here is a list of software/programs we were aware of that can conduct power anlaysis for growth curve models/multilevel models. >SAS power analysis Macros for a latent basis growth curve model The SAS macros estimate the power for testing nonlinear trajectory using the latent basis growth curve model. The macros ultilize both PROC MIXED and PROC NLMIXED to estimate statistical power. >SAS power analysis Macros for a quadratic growth curve model The SAS macros estimate the power of testing whether there is a quadratic term in the model by comparing a quadratic growth curve model and a linear growth curve model. >SAS power analysis Macros for a linear growth curve model with group information The macros estimate the power for a conditional linear growth curve model where the individual rates of change are predicted by the group information (covariates). The macros can be used to estimate the power of detecting the treatment effects. >The SAS power analysis Macros for an exponential growth curve model The macros estimate the power for evaluting parameters in an exponential growth curve model. R=10000 are recommended. In this example, the mean change between the iniital status and the asymptotic level is tested. It is recommended that a single replication of data is first tested to observe the behavior of convergence. The PROC NLMIXED is used here. The power estimation for the exponential growth curve model can be very slow. >SAS power analysis Macros for a linear growth curve model The macros estimate the power for evaluating the average rate of change. When there are missing data, R=5000 are recommended. The PROC MIXED is used to estimate the model parameters.

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