Package: tonymisc

Many of the methods and functions I have written about on this blog are available in my CRAN-contributed package tonymisc. As of its latest release (1.0.2), the tonymisc package contains methods that extend memisc's mtable() command to work with the following object types:

• gls() objects from package nlme.
• ivreg() objects from package AER.
• plm() and pgmm() objects from package plm.

The package also allows for mtable() output of robust standard errors, probit and logit marginal effects and IV-regression objects created using the 2SLS command iv() within the tonymisc package.

• mfx_me() coerces glm objects (probit or logit link) to interface conveniently with the mtable() command to report marginal effects.
• robust() coerces lm objects to interface conveniently mtable() to specify heteroskedasticity-consistent standard errors.  This command also allows the user to keep or drop variables from the mtable() output.
• iv() performs two-stage least squares regression and returns an object that conveniently allows the user to access first stage results and tests for relevance, both for single-endogenous regressor models (first stage F-test) and multiple-endogenous regressor models (test that the minimum canonical correlation is not zero, Anderson 2003).

Finally, the tonymisc library has several summary()-like commands available in the tonymisc library that report output to the screen for marginal effects, robust standard errors and IV models.

• mfx() reports Stata-like marginal effects to the screen when applied to a glm()-fit probit or logit model.
• summaryR() reports summary output for a lm()-fit model, but with robust standard errors (user-specified correction).
• sum_iv() reports select summary output (first stage, second stage, F-test, CC-test) to the screen for an iv()-fit model.

Leave a comment on this page if you have questions or suggestions for this package.