The simsam package, released earlier this year, allows versatile sample-size calculation (calculating sample size required to achieve given statistical power) using simulation for any method of analysis under any statistical model that can be programmed in Stata. Simulation is particularly...

Stata 13's new power command performs power and sample-size analysis. The power command expands the statistical methods that were previously available in Stata's sampsi command. I will demonstrate the power command and its additional features, including the support of multiple study scenarios...

This session introduces the use of the margins command to estimate the partial effects at the mean and the mean of the partial effects. Both the Stata syntax and the underlying statistical methods will be discussed. The presentation will also include some discussion of factor variables.

Multiple imputation is a method for trying to retrieve power lost by missing values in a dataset. In this session, I will demonstrate how the suite of mi commands introduced in Stata 11 can be used to impute data, estimate models, and pool results, as well as manage various forms of multiply...

This session focuses on the new Stata 12 command, mi impute chained, to perform multivariate imputation using chained equations (ICE), also known as sequential regression imputation. ICE is a flexible imputation technique for imputing various types of data. The variable-by-variable specification...

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Visualizing the true effect of a predictor over a range of values can be difficult for models that are not parameterized in their natural metric, such as logistic or (even more so) probit models. Interaction terms in such models cause even more fogginess. This illustrates how both the margins...

Data on twins or on other types of family structures (for example, nuclear families, siblings, cousins) can be used to estimate the proportion of variability in observed traits (or phenotypes) that is due to genes. The models are essentially multivariate regression models with residual...