Fit one MMRM and return one row

Fits the model described by a stress_spec() (optionally on alternative data or with alternative settings) and returns the treatment contrast at the contrast visit as a single row in the package's common schema. This is the engine every family function calls.

Usage

stress_fit(
  spec,
  data = NULL,
  label = spec$label,
  family = "base",
  kind = "alternative",
  is_base = is.null(data),
  note = "",
  covariates = spec$covariates,
  covariance = spec$covariance,
  method = spec$method,
  vcov = spec$vcov,
  at = list(),
  role = "sensitivity",
  weights = spec$weights
)

Arguments

spec

A stress_spec.

data

Alternative data set in the same layout as spec$data; NULL fits the spec's own data.

label, family, kind

Labels for the output row. kind is one of "alternative" (a counted alternative analysis), "deletion" (a leave-one-out refit), "search" (a point on a tipping-point grid) or "diagnostic" (fitted and shown but not counted).

is_base

TRUE when the row reproduces the pre-specified analysis exactly; such rows are not counted in a census.

note

Free text carried into the row.

covariates, covariance, method, vcov

Overrides of the spec's settings.

at

Named list of continuous covariates fixed at a value instead of their mean when forming the least-squares means (SAS LSMEANS ... AT).

role

"sensitivity" for an analysis that keeps the estimand and changes an assumption or a modelling choice; "supplementary" for one that targets a different estimand (ICH E9(R1)).

weights

LS-mean weighting, "equal" or "observed"; see stress_spec().

Value

A one-row data frame of class stress_rows with columns family, label, kind, role, is_base, converged, note, estimate, stderr, df, lcl, ucl, p, n_subj, n_obs, aicc, param (the numeric value of a continuous perturbation, NA otherwise), covariance, method, vcov, covariates, alpha.

Examples

spec <- stress_spec(mmrm::fev_data, "FEV1", "USUBJID", "AVISIT", "ARMCD", "PBO",
                    covariates = ~ RACE + SEX + FEV1_BL)
stress_fit(spec)
#>   family         label        kind        role is_base converged note estimate
#> 1   base pre-specified alternative sensitivity    TRUE      TRUE      4.404001
#>     stderr       df      lcl      ucl           p n_subj n_obs     aicc param
#> 1 1.673014 132.8789 1.094816 7.713186 0.009483085    197   537 3381.807    NA
#>   covariance        method                 vcov           covariates alpha
#> 1         us Kenward-Roger Kenward-Roger-Linear RACE + SEX + FEV1_BL  0.05