1. Psychometric meta-analysis. Stata’s new meta psycorr command performs meta-analysis for correlations that corrects for measurement error.

. meta psycorr r n, xreliability(rxx) yreliability(ryy)

direct and indirect range restriction

. meta psycorr r n, xuratios(ux) yuratios(uy) direct

dichotomization

. meta psycorr r n, xdich(px) ydich(py)

and small-sample bias

. meta psycorr r n, small

Continue your analysis with the meta suite to create forest plots, perform subgroup analysis, and more.

 

2. Moderating effects for heterogeneous DID two-way fixed-effects estimation. Stata’s new estat moderation postestimation command reports moderating effects of all or a subset of covariates included in the preceding heterogeneous difference-indifferences (DID) analysis.

Start with a heterogeneous DID two-way fixed effects analysis,

.xthdidregress twfe (outcome covariates) (treatment), group(group)

Test for the moderating effects of the covariates,

. estat moderation

Examine how the cohort- and time-varying ATETs vary with covariates.

 

3. Convert Word to HTML, EPUB, and more. Convert Word documents to other file formats using the new docx2 suite of commands. Use the putdocx suite of commands to create Word-compatible (.docx) files with Stata results and graphs.

. putdocx begin
….
. putdocx save myreport

Then convert to HTML

. docx2html myreport.docx

EPUB

. docx2epub myreport.docx

Markdown

. docx2md myreport.docx

Or plain text

. docx2txt myreport.docx

 

4. Test the proportional odds assumption after ordered logit regression. Stata’s new estat parallel postestimation command reports tests of the proportional odds assumption from the preceding ordinal logistic analysis.

When you fit an ordered logit regression,

. ologit outcome i.predictor, or

This model assumes the cumulative probability curves for each outcome category, plotted against a predictor, are parallel. Let’s test this assumption.

. estat parallel

Examine five tests of the proportional odds assumption: Brant, likelihood-ratio, score, Wald, and the Wolfe-Gould test.

 

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5. Discrete derivatives. New mata classes are available for discrete numerical derivatives.
   1. New Mata class DerivDiscreteDiff() computes the coefficients for a real, discrete numerical derivative using finite difference approximation.
   2. New Mata class DerivDiscretePartial() computes discrete numerical partial derivatives.

 

6. HDFE interactions. areg, ivregress 2sls, and xtreg, fe now allow factor-variable notation within option absorb(varlist). This is particularly useful when you wish to include interactions between high-dimensional fixed effects and continuous variables.

 

ADDITIONAL UPDATES

• Do-file Editor enhancements. The Do-file Editor now includes the following new features:
  • The Do-file Editor now supports bracket pair colorization for do- and ado-files. Bracket pair colorization is a feature where matching brackets — (), {}, and [] — are highlighted so that users can follow nested code structure at a glance. Each nesting level of brackets receives a distinct, reusable color, making it easy to trace from an opening (, {, or [ to its matching close bracket even in deeply nested, multiline expressions. Unmatched brackets are also displayed in a unique color, allowing them to stand out in the code. You can enable or disable bracket pair colorization in the Do-file Editor preferences as well as customize the different nesting level colors and the unmatched bracket color.
  • The checkbox Display > Show line guide has been added to the Do-file Editor’s preferences. When checked, it displays a line guide in the code-folding margin to denote where a code block begins and ends.
  • The dropdown box Advanced > Default action of Do button: has been added to the Do-file Editor’s preferences. The selected action will be executed when a user clicks the Do button in the Do-file Editor’s toolbar.
• hdidregress twfe and xthdidregress twfe have new option over(). Specifying over(timecohort) when cohort-time ATETs or cohort ATETs are requested and covariates are specified causes cohort-time-specific covariate means to be used in estimation. over(cohort), the default, yields the existing behavior of computing cohort-specific covariate means
• hdidregress twfe and xthdidregress twfe have new option noxinteract. Specifying noxinteract omits the interaction of specified covariates with difference-in-difference variables in the model so that covariates enter only as levels.
• New Mata class NDMatrix() defines an N-dimensional matrix.
• Mata function quantile() has two improvements:
  • Quantile estimator method “galton” is now supported as a synonym for “parzen“.
  • Method “inv_cdf” is renamed to “invedf“, and method “avg_inv_cdf” is renamed to “avginvedf“.  The previous names are still supported but no longer documented.