The post-estimation contract

The promises

Each cell carries exactly one promise:

Across the 792 cells: 378 agree, 169 refuse, 223 error, 22 return, 0 are known wrong, and 0 make no promise.

The test (tests/testthat/test_contract.R) runs each probe in a fresh R process holding estimatr and only the packages that probe needs, and runs the reference in a process that never loads estimatr. Isolation matters here: clubSandwich replaces estimatr’s bread() and model.frame() methods when it is loaded second, and performance registers a logLik() method for iv_robust, so a probe run beside them measures them rather than estimatr.

What decides a cell

One rule assigns every promise, so that the next generic is placed by it rather than by taste.

• A cell agrees wherever lm() or ivreg::ivreg() answers the same call and the fit stores what the answer needs. Where estimatr has a method, it returns that answer; where it has none, the fall-through must already be right.
• A cell refuses where the reference answers but the fit cannot, and the message names what the fit lacks: difference_in_means() and horvitz_thompson() store no residuals and no design, a fixed_effects fit does not store its absorbed design, a fit with several outcomes has one residual matrix for them all, and case-deletion diagnostics need leave-one-out refits that are not computed. A refusal replaces a NULL, a wrong number, or an unhelpful error with a sentence; it never replaces a working answer.
• A cell errors where no package should answer. logLik(), AIC(), and BIC() are the case to know: the estimators assume no distribution, and estimatr registers no logLik() on any class, because performance registers one for iv_robust() fits and a refusal on lm_robust() fits alone would make the answer depend on which package loaded last. The rest are generics that read internals an estimatr fit does not have, such as qr(), effects(), alias(), and anova().
• A cell returns where there is no reference to hold the value to: the fit-level generics on horvitz_thompson(), which has no reference fit; summary(fit)$fstatistic where the fit’s F statistic is a robust Wald statistic rather than lm()’s; and terms() and labels() on lm_lin(), whose translated formula has no counterpart.

The fits

All eleven are fit to one simulated dataset of 60 rows with a binary treatment z, a covariate x, a binary instrument iv, ten clusters g, a four-level factor f, weights w (three of them zero), and a second outcome y2.

The reference fits report classical variances, so a cell that concerns a variance, a standard error, or an interval refers instead to the variance estimatr reports by default: sandwich::vcovHC(ref, type = "HC2"), or clubSandwich::vcovCR(ref, type = "CR2") with Satterthwaite degrees of freedom for the clustered fits. lm_wt0’s variances refer to the same regression on its positive-weight rows, because sandwich counts zero-weight rows as observations. x_c is x centered, as lm_lin() centers it. dim and ht equal a regression on z only where a row says so.

The contract

Why each refusal

A refusal names what the fit lacks. These are the messages, and the cells that carry them:

Decisions

Some cells could reasonably have gone either way: whether df.residual() reports N - K or the cluster-adjusted degrees of freedom, whether logLik() on a robust fit should exist at all. Where a cell’s promise was a choice rather than a consequence, the maintainer’s decision is recorded beside it: