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.

ADOLIST: Stata module to manage lists of ado packages

-adolist- creates, installs and uninstalls lists of user ado packages.

ANOGI: Stata module to generate Analysis of Gini

anogi computes the "Analysis of Gini" for population sub-groups proposed by Frick et al. (2006; Sociological Methods and Research 34/4).

GSAMPLE: Stata module to draw a random sample

gsample draws a random sample from the data in memory. Simple random sampling (SRS) is supported, as well as unequal probability sampling (UPS), of which sampling with probabilities proportional to size (PPS) is a special case. Both methods, SRS and UPS/PPS, provide sampling with replacement and sampling without replacement. Furthermore, stratified sampling and cluster sampling is supported.

FAIRLIE: Stata module to generate nonlinear decomposition of binary outcome differentials

fairlie computes the nonlinear decomposition of binary outcome differentials proposed by Fairlie (1999, 2003).

KDENS: Stata module for univariate kernel density estimation

kdens produces univariate kernel density estimates and graphs the result. kdens supplements official Stata's kdensity. Important additions are: adaptive (i.e. variable bandwidth) kernel density estimation, several automatic bandwidth selectors including the Sheather-Jones plug-in estimator, pointwise variability bands and confidence intervals, boundary correction for variables with bounded domain, fast binned approximation estimation. Note that the moremata package, also available from SSC, is required.

RRLOGIT: Stata module to estimate logistic regression for randomized response data

rrlogit fits a maximum-likelihood logistic regression for randomized response data.