In this talk, we will show how to use simulations in Stata to explore to what extent and under what circumstances a test is problematic. We will illustrate this for a set of tests of the parallel regression assumption in ordered logit and probit models: the Brant, likelihood ratio, Wald, score,...

In this talk, I aim to discuss tools to compare the observed distribution of a variable with the theoretical distribution assumed by a model. In particular, I will focus on the situation where a model assumes a certain distribution for the explained/dependent/y variable and one or more...

Sometimes we have multiple measures of the same concept. Combining the information of these multiple measures would allow us to improve the measurement. When combining the information from different indicators one needs to distinguish between two types of relationships between the observed...

Sometimes one wants to model the effect of a variable as a nonlinear smooth curve. A convenient choice for such a curve is a restricted cubic spline. This option has existed in Stata for a while through user-written programs, but as of Stata 10, the mkspline command in combination with the cubic...

Many of us, at some point, have received a comment from a member of the audience, a reviewer, or an advisor who thinks the technique used is bad/biased/evil and who knows of some new fancy method that solves the problem. In those cases, you often want to know two things: 1) How big is the...

Stata has for a long time the capability of imposing the constraint that parameters are a linear function of one another. It does not have the capability to impose the constraint that if a set of parameters change (due to interaction terms) they will maintain the relative differences among them....

In this presentation, I discuss a method by Erikson et al. (2005) for decomposing a total effect in a logit model into direct and indirect effects, and I propose a generalization of this method. Consider an example where social class has an indirect effect on attending college through academic...

When dealing with response variables that are proportions, people often use regress. This approach can be problematic since the model can lead to predicted proportions less than zero or more than one and errors that are likely to be heteroskedastic and nonnormally distributed. This talk will...

In this talk, I will discuss some techniques available in Stata for analyzing dependent variables that are proportions. I will discuss four programs: betafit, glm, dirifit, and fmlogit. The first two deal with situations where we want to explain only one proportion, while the latter two deal...