Review of Maximum Likelihood Estimation with Stata by Gould, Pitblado, and Sribney

The new book by Gould, Pitblado, and Sribney (2003) is reviewed. Copyright 2003 by StataCorp LP.maximum likelihood, Stata programming

Report to Users / Wishes and Grumbles

These minutes summarize StataCorp president Bill Gould's remarks in a Report to Users, and a "Wishes and Grumbles" session in which users made suggestions to Messrs Gould and Gutierrez.

Variance estimation for the instrumental variables approach to measurement error in generalized linear models

This paper derives and gives explicit formulas for a derived sandwich variance estimate. This variance estimate is appropriate for generalized linear additive measurement error models fitted using instrumental variables. We also generalize the known results for linear regression. As such, this article explains the theoretical justification for the sandwich estimate of variance utilized in the software for measurement error developed under the Small Business Innovation Research Grant (SBIR) by StataCorp. The results admit estimation of variance matrices for measurement error models where there is an instrument for the unknown covariate. Copyright 2003 by StataCorp LP.sandwich estimate of variance, measurement error, White's estimator, robust variance, generalized linear models, instrumental variables

Measurement error, GLMs, and notational conventions

This paper introduces additive measurement error in a generalized linear-model context. We discuss the types of measurement error along with their effects on fitted models. In addition, we present the notational conventions to be used in this and the accompanying papers. Copyright 2003 by StataCorp LP.generalized linear models, transportability, measurement error

Thirty-Three Stata Tips

Since 2003, the Stata Journal has published Stata Tips on special issues in data analysis with Stata. Now Thirty-three Stata Tips compiles these useful guides into a compact tome for ease of reference. In keeping with the Stata spirit, Tips are from Stata users and StataCorp employees alike and will serve as guideposts for both new and experienced users.data management, statistics, graphics, Stata

A conversation with William Gould

William Gould is President of StataCorp. He was born in Burbank, California, on January 21, 1952. He received a B.A. in economics from UCLA in 1974 and a C.Phil. in economics from UCLA in 1977, after initially majoring in physics and then engineering. He studied economics in the Ph.D. program at UCLA and was simultaneously a Research Fellow at The Rand Corporation. He did not turn in his dissertation in labor economics before becoming a Senior Research Associate at the National Bureau of Economic Research in Stanford, California, in 1977. In 1979, he become a Senior Economist at Unicon Research Corporation in Los Angeles, a company that he helped to found. He cofounded and served as Vice-President of Computing Resource Center in 1982, the company that went on to develop Stata. Bill became President of CRC in 1990 and, in 1993, CRC was renamed StataCorp. Copyright 2005 by StataCorp LP.

Speaking Stata: Problems with tables, Part I

Tables in some form or another are part and parcel of data management and analysis. The main general-purpose tabulation commands, tabulate, table, and tabstat, are reviewed and compared. When these do not provide a tabulation solution, one key strategy is to prepare the material for tabulation as a set of variables, after which the table itself can be presented with tabdisp or list. This is the first of two papers on this topic. Copyright 2003 by StataCorp LP.tables, tabulate, table, tabstat, tabdisp, list

From the help desk

Welcome to From the help desk. From the help desk is written by the people in Technical Services at StataCorp and deals with issues that they have found to be of concern to a large fraction of Stata users. It is the rare column in this series that deals with sophisticated programming issues because such issues, by definition, are not of concern to a large fraction of Stata users. From the help desk discusses the use of sophisticated programs and the use of sophisticated statistics. Copyright 2001 by Stata Corporation.internet, web, ado-files, Stata executable installation, updates, downloading, user-written additions, packages, search, find

From the help desk: Polynomial distributed lag models

Polynomial distributed lag models (PDLs) are finite-order distributed lag models with the impulse-response function constrained to lie on a polynomial of known degree. You can estimate the parameters of a PDL directly via constrained ordinary least squares, or you can derive a reduced form of the model via a linear transformation of the structural model, estimate the reduced-form parameters, and recover estimates of the structural parameters via an inverse linear transformation of the reduced-form parameter estimates. This article demonstrates both methods using Stata. Copyright 2004 by StataCorp LP.polynomial distributed lag, Almon, Lagrangian interpolation polynomials

Speaking Stata: Graphing categorical and compositional data

A variety of graphs have been devised for categorical and compositional data, ranging from widely familiar to more unusual displays. Both official Stata commands and user-written programs are available. After a stacking trick for binary responses is explained, bar charts and related displays for cross-tabulations are discussed in detail. Tips and tricks are introduced for plotting cumulative distributions of graded (ordinal) data. Triangular plots are explained for threeway compositions, such as three proportions or percentages. Copyright 2004 by StataCorp LP.graphics, categorical data, binary data, nominal data, ordinal data, grades, compositional data, cross-tabulations, bar charts, cumulative distributions, logit scale, catplot, tabplot, tableplot, distplot, mylabels, triplot