Introduction to treatment effects in Stata: Part 2
This post was written jointly with David Drukker, Director of Econometrics, StataCorp. In our last post, we introduced the concept of treatment effects and demonstrated four of the treatment-effects...
View ArticleMaximum likelihood estimation by mlexp: A chi-squared example
Overview In this post, I show how to use mlexp to estimate the degree of freedom parameter of a chi-squared distribution by maximum likelihood (ML). One example is unconditional, and another example...
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Efficiency comparisons by Monte Carlo simulation
Overview In this post, I show how to use Monte Carlo simulations to compare the efficiency of different estimators. I also illustrate what we mean by efficiency when discussing statistical estimators....
View ArticleEstimating parameters by maximum likelihood and method of moments using mlexp...
\(\newcommand{\epsilonb}{\boldsymbol{\epsilon}} \newcommand{\ebi}{\boldsymbol{\epsilon}_i} \newcommand{\Sigmab}{\boldsymbol{\Sigma}} \newcommand{\Omegab}{\boldsymbol{\Omega}}...
View ArticleProbit model with sample selection by mlexp
Overview In a previous post, David Drukker demonstrated how to use mlexp to estimate the degree of freedom parameter in a chi-squared distribution by maximum likelihood (ML). In this post, I am going...
View ArticleFixed Effects or Random Effects: The Mundlak Approach
Today I will discuss Mundlak’s (1978) alternative to the Hausman test. Unlike the latter, the Mundlak approach may be used when the errors are heteroskedastic or have intragroup correlation. What is...
View ArticleUsing mlexp to estimate endogenous treatment effects in a probit model
I use features new to Stata 14.1 to estimate an average treatment effect (ATE) for a probit model with an endogenous treatment. In 14.1, we added new prediction statistics after mlexp that margins can...
View Articlextabond Cheat Sheet
Random-effects and fixed-effects panel-data models do not allow me to use observable information of previous periods in my model. They are static. Dynamic panel-data models use current and past...
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Understanding the generalized method of moments (GMM): A simple example
\(\newcommand{\Eb}{{\bf E}}\)This post was written jointly with Enrique Pinzon, Senior Econometrician, StataCorp. The generalized method of moments (GMM) is a method for constructing estimators,...
View ArticleUsing mlexp to estimate endogenous treatment effects in a heteroskedastic...
I use features new to Stata 14.1 to estimate an average treatment effect (ATE) for a heteroskedastic probit model with an endogenous treatment. In 14.1, we added new prediction statistics after mlexp...
View ArticleCompeting risks in the Stata News
The fourth quarter Stata News came out today. Among other things, it contains an article by Bobby Gutierrez, StataCorp’s Director of Statistics, about competing risks survival analysis. If any of you...
View ArticleIncluding covariates in crossed-effects models
The manual entry for xtmixed documents all the official features in the command, and several applications. However, it would be impossible to address all the models that can be fitted with this command...
View ArticlePositive log-likelihood values happen
From time to time, we get a question from a user puzzled about getting a positive log likelihood for a certain estimation. We get so used to seeing negative log-likelihood values all the time that we...
View ArticleUse poisson rather than regress; tell a friend
Do you ever fit regressions of the form ln(yj) = b0 + b1x1j + b2x2j + … + bkxkj + εj by typing . generate lny = ln(y) . regress lny x1 x2 … xk The above is just an ordinary linear regression except...
View ArticleMultilevel random effects in xtmixed and sem — the long and wide of it
xtmixed was built from the ground up for dealing with multilevel random effects — that is its raison d’être. sem was built for multivariate outcomes, for handling latent variables, and for estimating...
View ArticleBuilding complicated expressions the easy way
Have you every wanted to make an “easy” calculation–say, after fitting a model–and gotten lost because you just weren’t sure where to find the degrees of freedom of the residual or the standard error...
View ArticleComparing predictions after arima with manual computations
Some of our users have asked about the way predictions are computed after fitting their models with arima. Those users report that they cannot reproduce the complete set of forecasts manually when the...
View ArticleUsing Stata’s SEM features to model the Beck Depression Inventory
I just got back from the 2012 Stata Conference in San Diego where I gave a talk on Psychometric Analysis Using Stata and from the 2012 American Psychological Association Meeting in Orlando. Stata’s...
View ArticleMultilevel linear models in Stata, part 1: Components of variance
In the last 15-20 years multilevel modeling has evolved from a specialty area of statistical research into a standard analytical tool used by many applied researchers. Stata has a lot of multilevel...
View ArticleMultilevel linear models in Stata, part 2: Longitudinal data
In my last posting, I introduced you to the concepts of hierarchical or “multilevel” data. In today’s post, I’d like to show you how to use multilevel modeling techniques to analyse longitudinal data...
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