Explain why an alternative analysis moved — stress

For one row of a census (an alternative that crossed alpha, say), attributes the difference between its estimate and the pre-specified estimate to subjects. Each subject's influence is the change in the contrast when that subject is removed, computed under the pre-specified settings and again under the alternative's settings; the difference of the two influences says how much more (or less) that subject drives the result under the alternative. Subjects are ranked by the absolute difference.

Usage

stress_explain(spec, row, data = NULL, top = 10, cores = 1L)

Arguments

spec: A stress_spec().
row: One row of a stress_census or stress_rows data frame.
data: The alternative's data set, if it differs from the spec's.
top: Number of subjects to print.
cores: Number of worker processes; 1 fits sequentially.

Value

A data frame of class stress_explanation with one row per subject: subject, arm, n_visits, infl_base, infl_alt, difference, sorted by absolute difference; the row explained is attr(, "row") and the two full-data estimates are attr(, "estimates").

Details

The alternative's model settings are read from the row (covariance, method, vcov, covariates). For an alternative that used different data, pass that data as data.

Examples

small <- mmrm::fev_data[mmrm::fev_data$USUBJID %in% paste0("PT", 1:30), ]
spec <- stress_spec(small, "FEV1", "USUBJID", "AVISIT", "ARMCD", "PBO", covariates = ~ FEV1_BL,
                    covariance = "cs", method = "Satterthwaite", vcov = "Asymptotic")
cen <- stress_census(spec, stress_covariates(spec))
stress_explain(spec, cen[1, ], top = 5)
#> Alternative: covariate set / without FEV1_BL
#> Estimate 5.735 (pre-specified) -> 7.913 (alternative); shift 2.18
#> Subjects whose influence changes most (influence = estimate minus estimate without the subject):
#>  subject arm n_visits infl_base infl_alt difference
#>     PT15 PBO        2   0.00533    0.690      0.684
#>     PT17 PBO        2  -0.18286    0.467      0.650
#>     PT16 PBO        2   0.05930   -0.370     -0.429
#>      PT2 PBO        3  -0.25015   -0.678     -0.427
#>      PT3 PBO        2   1.52624    1.113     -0.413