A widespread tool in the context of a point null hypothesis significance testing framework is the computation of statistical power, especially in the planning stage of quantitative studies. However, asymptotic power formulas are often not readily available for certain tests, or are too...

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...

The purpose of this presentation is to introduce a new user-written code that allows for measuring poverty in a panel of individuals. It complements existing poverty codes for a cross-section of individuals (e.g. povdeco, poverty) by producing a new family of indices proposed by Gradín, Cantó...

As with most programming languages, there can be multiple ways to do a task in Stata. Using modern CPUs with adequate memory, most Stata data processing commands run so quickly on small- or moderate-sized data sets that it is impossible to tell whether one command performs more efficiently than...

We use Stata to obtain the linear maximum entropy estimator developed by Golan, Judge and Miller (1996). We use the STATA optimize function to illustrate maximum entropy estimation in an unrestricted linear regression model. Next, we estimate the model with parameter inequality restrictions to...

The paper aims at analyzing the Exchange Rate Pass-Through mechanism for the Mexican economy and is carried out using STATA under two time series frameworks. The first framework is a recursive structural VAR (SVAR) model which, unlike the traditional VAR model, allows us to impose additional...

The stereotype logistic regression model for a categorical dependent variable is often described as a compromise between the multinomial and proportional-odds logistic models, and has many attractive features. Among these are the ability to test the adequacy of the model fit compared to the...

Introducing generalized SEM: (1) SEM with generalized linear response variables, and (2) SEM with multilevel mixed effects, whether linear or generalized linear. Generalized linear response variables mean you can now fit probit, logit, Poisson, multinomial logistic, ordered logit, ordered...

Klein and Vella (2010) propose an estimator to fit a triangular system of two simultaneous linear equations with a single endogenous regressor. Models of this form are generally analyzed with two-stage least squares or IV methods, which require one or more exclusion restriction. In practice, the...

Measurement invariance is a very important requisite in multiple group structural equation modeling. It attempts to verify that the factors are measuring the same underlying latent constructs within each group. The presentation will show the use of the sem command in assessing six types of...