Showing 1 - 10 of 297
Stata 11 has the new command gmm for estimating parameters by generalized method of moments (GMM). gmm can estimate the parameters of linear and nonlinear models for cross-sectional, panel, and time-series data. In this presentation, I provide an introduction to GMM and to the gmm command
Persistent link: https://www.econbiz.de/10008507999
In this talk, I will provide a quick introduction to estimators for the parameters of spatial-autoregressive models and a quick introduction to a suite of user-written Stata commands for managing spatial data and parameter estimation.
Persistent link: https://www.econbiz.de/10005101351
Many researchers need to estimate panel data models in which either the idiosyncratic term is autocorrelated or the model includes a lagged dependent variable. This talk will review some of the estimation and inference methods that have appeared in the econometric literature to deal with these...
Persistent link: https://www.econbiz.de/10005053350
In this talk, I will review dynamic panel-data analysis and how to perform it using Stata. I also cover static models with predetermined variables. For each model discussed, I review the econometrics and then show how to perform the estimation using Stata.
Persistent link: https://www.econbiz.de/10005028089
Stata 11 has a new command, gmm, for estimating parameters by the generalized method of moments (GMM). gmm can estimate the parameters of linear and nonlinear models for cross-sectional, panel, and time-series data. In this presentation, I provide an introduction to GMM and to the gmm command.
Persistent link: https://www.econbiz.de/10008455639
This paper presents an implementation of matching estimators for average treatment effects in Stata. The nnmatch command allows you to estimate the average effect for all units or only for the treated or control units; to choose the number of matches; to specify the distance metric; to select a...
Persistent link: https://www.econbiz.de/10005583256
I present 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 of ICE allows...
Persistent link: https://www.econbiz.de/10009319515
Splines, including polynomials, are traditionally used to model nonlinear relationships involving continuous predictors. However, when they are included in linear models (or generalized linear models), the estimated parameters for polynomials are not easy for nonmathematicians to understand, and...
Persistent link: https://www.econbiz.de/10009320956
We will discuss SEM (structural equation modeling), not from the perspective of the models for which it is most often used--measurement models, confirmatory factor analysis, and the like--but from the perspective of how it can extend other estimators. From a wide range of choices, we will focus...
Persistent link: https://www.econbiz.de/10009320959
One of the aims of a phase I trial in oncology is to find the maximum tolerated dose. A set of doses is administered to participants starting from the lowest dose in increasing steps. To do this safely, the toxicity of each dose is assessed, and a decision is made about whether to proceed with...
Persistent link: https://www.econbiz.de/10009320960