18 packages found (Stata Journal listed first) ---------------------------------------------- @net:describe st0741, from(http://www.stata-journal.com/software/sj24-1)!st0741 from http://www.stata-journal.com/software/sj24-1@ SJ24-1 st0741. Nearly collinear robust ... / Nearly collinear robust instrumental-variables / regression / by Alwyn Young, London School of Economics, / London, U.K. / Support: a.young@lse.ac.uk / After installation, type help {cmd:pariv} / DOI: 10.1177/1536867X241233668 @net:describe st0158, from(http://www.stata-journal.com/software/sj9-1)!st0158 from http://www.stata-journal.com/software/sj9-1@ SJ9-1 st0158. A general-purpose method for two-group... / A general-purpose method for two-group randomization tests / by Johannes Kaiser, Lab. for Experimental Economics, / Univ. of Bonn, Germany / Michael G. Lacy, Sociology Dept., Colo. State. Univ., / Fort Collins, CO, @net:describe truncreg, from(http://www.stata.com/users/rcong)!truncreg from http://www.stata.com/users/rcong@ truncreg. Truncated regression (updates to STB-52 sg122) / Program by Ronna Cong, stata Corporation / STB 52 distribution, November 1999. / / ^truncreg^ is used to estimate a regression model for data from / a truncated normal distribution. See STB-52 sg122 for complete @net:describe cndnmb3, from(http://fmwww.bc.edu/RePEc/bocode/c)!cndnmb3 from http://fmwww.bc.edu/RePEc/bocode/c@ 'CNDNMB3': module to calculate condition number of regressor matrix / cndnmb3 calculates the maximal condition number of a matrix of / regressors. This statistic (the ratio of largest to smallest / eigenvalue) is an unbounded measure of collinearity, or / @net:describe coldiag, from(http://fmwww.bc.edu/RePEc/bocode/c)!coldiag from http://fmwww.bc.edu/RePEc/bocode/c@ 'COLDIAG': module to perform BWK regression collinearity diagnostics / Coldiag is an implementation of the regression collinearity / diagnostic procedures found in Belsley, Kuh, and Welsch (1980). / These procedures examine the "conditioning" of the matrix of / independent variables. @net:describe coldiag2, from(http://fmwww.bc.edu/RePEc/bocode/c)!coldiag2 from http://fmwww.bc.edu/RePEc/bocode/c@ 'COLDIAG2': module to evaluate collinearity in linear regression / coldiag2 is an implementation of the regression collinearity / diagnostic procedures found in Belsley, Kuh, and Welsch (1980). / These procedures examine the "conditioning" of the matrix of / independent variables. This @net:describe fgtest, from(http://fmwww.bc.edu/RePEc/bocode/f)!fgtest from http://fmwww.bc.edu/RePEc/bocode/f@ 'FGTEST': module to Compute Farrar-Glauber Multicollinearity Chi2, F, t Tests / fgtest Computes Farrar-Glauber Multicollinearity Chi2, F, t / Tests / KW: regression / KW: Multicollinearity / KW: Farrar-Glauber test / Requires: Stata version 10 / Distribution-Date: 20120208 / Author: Emad @net:describe ivpermute, from(http://fmwww.bc.edu/RePEc/bocode/i)!ivpermute from http://fmwww.bc.edu/RePEc/bocode/i@ 'IVPERMUTE': module to estimate nearly collinear robust instrumental variables regression / ivpermute estimates 2SLS coefficients using formulas based upon / the partitioned regression. Estimates using the partitioned / regression are more robust to near collinearity among the / @net:describe ivvif, from(http://fmwww.bc.edu/RePEc/bocode/i)!ivvif from http://fmwww.bc.edu/RePEc/bocode/i@ 'IVVIF': module to report variance inflation factors after IV / ivvif extends Stata's official vif/estat vif command, which / reports variance inflation factors. It differs in two ways. As / well as working after regress, it can run after instrumented / regressions done with ivreg or @net:describe lmcol, from(http://fmwww.bc.edu/RePEc/bocode/l)!lmcol from http://fmwww.bc.edu/RePEc/bocode/l@ 'LMCOL': module to compute OLS Multicollinearity Diagnostic Tests / lmcol computes OLS Multicollinearity Diagnostic Tests / KW: collinearity / KW: Farrar-Glauber / KW: Theil / Requires: Stata version 11 / Distribution-Date: 20121006 / Author: Emad Abd Elmessih Shehata, @net:describe paran, from(http://fmwww.bc.edu/RePEc/bocode/p)!paran from http://fmwww.bc.edu/RePEc/bocode/p@ 'PARAN': module to compute Horn's test of principal components/factors / paran is an implementation of Horn's technique for evaluating the / components or factors retained in a principal components analysis / (PCA) or a common factor analysis. According to Horn, a common / interpretation @net:describe pariv, from(http://fmwww.bc.edu/RePEc/bocode/p)!pariv from http://fmwww.bc.edu/RePEc/bocode/p@ 'PARIV': module to perform nearly-collinear robust instrumental-variables regression / pariv fits a partitioned 2SLS regression that is more robust to / near collinearity than existing Stata 2SLS commands. / KW: instrumental variables / KW: robust / KW: collinearity / Requires: Stata @net:describe perturb, from(http://fmwww.bc.edu/RePEc/bocode/p)!perturb from http://fmwww.bc.edu/RePEc/bocode/p@ 'PERTURB': module to evaluate collinearity and ill-conditioning / perturb is a tool for assessing the impact of small random / changes (perturbations) to variables on parameter estimates. It / is an alternative for collinearity diagnostics such as vif, / collin, coldiag, @net:describe ranktest, from(http://fmwww.bc.edu/RePEc/bocode/r)!ranktest from http://fmwww.bc.edu/RePEc/bocode/r@ 'RANKTEST': module to test the rank of a matrix / ranktest implements various tests for the rank of a matrix. / Tests of the rank of a matrix have many practical applications. / For example, in econometrics the requirement for identification / is the rank condition, which states that @net:describe regcheck, from(http://fmwww.bc.edu/RePEc/bocode/r)!regcheck from http://fmwww.bc.edu/RePEc/bocode/r@ 'REGCHECK': module to examine regression assumptions / This routine examines several underlying assumptions after / regression. It invokes the Breusch-Pagan test, computes Variance / Inflation Factors, the Shapiro-Wilk test, the linktest, the RESET / test and Cook's distance. / @net:describe ridgereg, from(http://fmwww.bc.edu/RePEc/bocode/r)!ridgereg from http://fmwww.bc.edu/RePEc/bocode/r@ 'RIDGEREG': module to compute Ridge Regression Models / ridgereg estimates Ridge Regression Models / KW: regression / KW: Multicollinearity / KW: ridge / KW: Ridge Regression / KW: Farrar-Glauber Multicollinearity tests / KW: Variance Inflation Factor / KW: Condition Index / KW: Theil R2 @net:describe theilr2, from(http://fmwww.bc.edu/RePEc/bocode/t)!theilr2 from http://fmwww.bc.edu/RePEc/bocode/t@ 'THEILR2': module to compute Theil R2 Multicollinearity Effect / theilr2 computes Theil R2 Multicollinearity Effect / KW: regression / KW: Theil R2 Multicollinearity Effect / KW: collinearity / Requires: Stata version 10 / Distribution-Date: 20120208 / Author: Emad Abd Elmessih Shehata, @net:describe collin, from(https://stats.oarc.ucla.edu/stat/stata/ado/analysis)!collin from https://stats.oarc.ucla.edu/stat/stata/ado/analysis@ collin. Collinearity Diagnostics / Philip B. Ender / Statistical Computing and Consulting / UCLA Office of Academic Computing / ender@@ucla.edu / STATA ado and hlp files in the package / distribution-date: 20101123 8 references found in tables of contents ---------------------------------------- @net:from http://www.stata-journal.com/software/sj24-1/!http://www.stata-journal.com/software/sj24-1/@ Stata Journal volume 24, issue 1 / Update: Estimating text regressions using / txtreg_train / Update: Nice axis labels for general scales / Use Windows PowerShell to send email / Open the online help file or PDF / documentation for a specific command in the / default browser / Update: @net:from http://fmwww.bc.edu/RePEc/bocode/c/!http://fmwww.bc.edu/RePEc/bocode/c/@ module to implement machine learning classification in Stata / module to implement machine learning classification in Stata / module to generate calendar / module to estimate proportions and means after survey data have been calibrated to population totals / module for inverse regression and @net:from http://fmwww.bc.edu/RePEc/bocode/f/!http://fmwww.bc.edu/RePEc/bocode/f/@ module for the estimation of marginal effects with transformed covariates / module to score Foot and Ankle Ability Measure / module for plots for each subset with rest of the data as backdrop / module to extract factor values from a label variable created by parmest / module to merge a list @net:from http://fmwww.bc.edu/RePEc/bocode/i/!http://fmwww.bc.edu/RePEc/bocode/i/@ module to import International Aid Transparency Initiative data / module to compute measures of interaction contrast (biological interaction) / module to compute Interaction Effects in Linear and Generalized Linear Models / module that computes models 2 and 3 of the intra-class @net:from http://fmwww.bc.edu/RePEc/bocode/l/!http://fmwww.bc.edu/RePEc/bocode/l/@ module to automatically manage datasets obtained from US Census 2000 and World Development Indicators databases / module to produce syntax to label variables and values, given a data dictionary / module to report numeric variables with values lacking value labels / module to list value labels / @net:from http://fmwww.bc.edu/RePEc/bocode/p/!http://fmwww.bc.edu/RePEc/bocode/p/@ module to calculate confidence limits of a regression coefficient from the p-value / module to perform Page's L trend test for ordered alternatives / module to create paired datasets from individual-per-row data / module for plots of paired observations / module to import network data in Pajek's @net:from http://fmwww.bc.edu/RePEc/bocode/t/!http://fmwww.bc.edu/RePEc/bocode/t/@ module to report Mean Comparison for variables between two groups with formatted table output in DOCX file / module to perform Tukey's Two-Way Analysis by Medians / module to produce a one-way table as a matrix / module to handle two-way tables with percentages / module to handle @net:from https://stats.oarc.ucla.edu/stat/stata/ado/analysis/!https://stats.oarc.ucla.edu/stat/stata/ado/analysis/@ Welcome to UCLA Academic Technology Services Stata programs. / These programs include tools for data analysis. / These include programs from the Stata Technical Bulletin, / courtesy of, and copyright, Stata Corporation. / For more information about these programs, see / our web