surveycore v0.4.0

New features

• survey_glm() fits survey-weighted generalized linear models for all five
  design classes (survey_taylor, survey_replicate, survey_srs,
  survey_twophase, survey_calibrated); returns a survey_glm_fit object
  with design-based (Binder 1983 sandwich) standard errors and degrees of
  freedom.

• clean() converts a survey_glm_fit to a tidy survey_glm_tidy tibble
  with one row per coefficient, design-based confidence intervals, structured
  metadata, and optional reference rows for factor predictors.

• survey_glm_fit objects support 20 S3 methods: print(), summary(),
  coef(), vcov(), predict(), fitted(), residuals(), confint(),
  formula(), terms(), model.matrix(), model.frame(), deviance(),
  df.residual(), nobs(), hatvalues(), logLik(), AIC(), BIC(), and
  update().

• survey_glm_fit integrates with the marginaleffects package; when
  marginaleffects is installed, avg_slopes(), avg_predictions(), and the
  full marginaleffects API work directly on survey_glm_fit objects.

• broom::tidy() is supported for survey_glm_fit objects via a shim that
  delegates to clean().

• as_survey_rep() has been renamed to as_survey_repweights() to avoid a
  namespace clash with the srvyr package.

Bug fixes

• as_survey_twophase() variance estimation (method = "approx" and
  "full") now uses the correct PSU-level Phase 2 stratum sampling fraction
  instead of a row-level fraction, resolving an approximately 2× variance
  underestimation.