![]() ![]() If I were to use the ubiquitous example of “children in schools” the Level 1 sample would be the children (individuals within a cluster) and the Level 2 sample would be the schools (number of clusters). What **you**, as the user, need to provide is the following: When you open the app, here’s how it looks: It uses the Wald test statistic for the fixed effect predictors and a 1-degree-of-freedom likelihood-ratio test for the random effects (← yes, I know this is conservative but it’s the fastest one to implement). The app will give you the power for each individual covariate/predictor AND the variance component for the intercept (if you choose to fit a random-intercept model) or the slope (if you choose to fit a model with both a random intercept and a random slope). Bernoulli-distributed) but with the option to manipulate the probability parameter p to simulate imbalance of the groups. It currently only supports binary categorical covariates/predictors (i.e. The continuous predictors come in two types: normally distributed or skewed (i.e. This app will perform computer simulations to estimate power for multilevel logistic regression models allowing for continuous or categorical covariates/predictors and their interaction. This app is hosted on a free server and it can only accommodate a certain number of people every day. If the problem still persists that means too many people have tried to access it during the day and the server has shut down. WARNING (2): If you keep getting a ‘disconnected from server’ error, close down your browser and open a new window. If it appears ‘stuck’ but you haven’t got an error it means the simulation is still running on the background. Do not close your web browser unless it gives you an error. ![]() WARNING (1): This app can take a little while to run. If you plan on using this app, it would be a good idea to cite it □ The relationship between statistical power and predictor distribution in multilevel logistic regression: a simulation-based approach ::UPDATE:: A published article introducing this app is now online in BMC-Medical Research Methodology. ![]()
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