Output processing and automatic reporting with Stata

This talk illustrates how results from various Stata commands can be processed efficiently for inclusion in customized reports. A two-step procedure is proposed in which results are gathered and archived in the first step and then tabulated in the second step. Such an approach disentangles the tasks of computing results (which may take long) and preparing results for inclusion in presentations, papers, and reports (which you may have to do over and over). Examples using results from model estimation commands and various other Stata commands such as tabulate, summarize, or correlate are presented. Users will also be shown how to dynamically link results into word processors or into LaTeX documents.

Creating LaTeX documents from within Stata

In this presentation, I present a new user package called texdoc. texdoc can be used to create a LaTeX document from within Stata in a weaving fashion. This is especially useful if you want to produce a LaTeX document that contains Stata output, such as a Stata Journal article or solutions to statistics homework assignments. I will provide examples illustrating the usage of texdoc.

Relative Distribution Methods in Stata

The concept of the relative density seems like a fruitful nonparametric approach to studying distributional differences between groups (Handcock and Morris 1999), yet it appears that the technique has gone more or less unnoticed in applied social science research. A scarcity of canned software might be one of the reasons the method is underutilized. Therefore, I present a new Stata command called reldist to plot the relative density, decompose distributional differences into location and shape effects, and compute relative distribution summary measures. The command is illustrated by an application comparing earnings by sex.

Adolists: A new concept for Stata

A new package called adolist is presented. adolist is a tool to create, install, and uninstall lists of user ado-packages (“adolists”). For example, adolist can create a list of all user packages installed on a system and then install the same packages on another system. Moreover, ado-list can be used to put together thematic lists of packages such as, say, a list on income inequality analysis or time-series add-ons, or the list of “41 user ados everyone should know”. Such lists can then be shared with others, who can easily install and uninstall the listed packages using the adolist command.

Ado-lists: A new concept for Stata

A new command called adolist is presented. adolist is a tool to create, install, and uninstall lists of user ado-packages (“adolists”). For example, adolist can create a list of all user packages installed on a system and then install the same packages on another system. Moreover, ado-list can be used to put together thematic lists of packages such as, say, a list on income inequality analysis or time-series add-ons, or the list of “41 user ados everyone should know”. Such lists can then be shared with others, who can easily install and uninstall the listed packages using the adolist command.

TEXDOC: Stata module to create a LaTeX document including Stata output

texdoc provides tools to create a LaTeX document from within Stata in a weaving fashion. This is especially useful if you want to produce a LaTeX document that contains Stata output, such as, e.g., a Stata Journal article or solutions to statistics homework assignments.

TABLETUTORIAL: Stata module to provide tutorial on automated table generation and reporting

-tabletutorial- illustrates how Stata can be used to export statistical results and generate customized reports. Part 1 explains how results from Stata routines can be accessed and how they can be exported using the -file- comand or a wrapper such as, e.g., -mat2txt-. Part 2 shows how model estimation results can be archived using -estwrite- and how models can be tabulated and exported to LaTeX, MS Excel, or MS Word using -estout-. Part 3 illustrates how to set up automatic reports in LaTeX or MS Word. The tutorial is based on a talk given at CEPS/INSTEAD in Luxembourg in October 2008. After install, type -help tabletutorial- to start the tutorial (in Stata 8, type -whelp tabletutorial-). The -mat2txt-, -estwrite-, and -estout- packages, also available from SSC, are required to run the examples.

PSPLINE: Stata module providing a penalized spline scatterplot smoother based on linear mixed model technology

Pspline uses xtmixed to fit a penalized spline regression and plots the smoothed function. Additional covariates can be specified to adjust the smooth and plot partial residuals.

NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model

LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression

logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth

RRREG: Stata module to estimate linear probability model for randomized response data

rrreg fits a linear probability model for randomized response data

OAXACA: Stata module to compute the Blinder-Oaxaca decomposition

-oaxaca- computes the so-called Blinder-Oaxaca decomposition, which is often used to analyze wage gaps by sex or race. Older versions of this routine are available as -oaxaca9- and -oaxaca8-.

DIGDIS: Stata module to analyze the distribution of digits

digdis tabulates the distribution of digits of the specified variables, performs goodness-of-fit tests against a reference distribution and, optionally, graphs the distributions. The default is to tabulate the first (nonzero) digit and to test against Benford's law. The moremata package and the mgof package, also available from SSC, are required.

MGOF: Stata module to perform goodness-of-fit tests for multinomial data

mgof computes goodness-of-fit tests for the distribution of a discrete (categorical, multinomial) variable. The default is to perform classical large sample chi-squared approximation tests based on Pearson's X2 statistic and the log likelihood ratio (G2) statistic or a statistic from the Cressie-Read family. Alternatively, mgof computes exact tests using Monte Carlo methods or exhaustive enumeration. A Kolmogorov-Smirnov test for discrete data is also provided. The moremata package, also available from SSC, is required.