g_mmrm_diagnostic {tern.mmrm}

Diagnostic Plots for MMRM

Description

This function produces diagnostic plots.

Usage

g_mmrm_diagnostic(
  object,
  type = c("fit-residual", "q-q-residual"),
  z_threshold = NULL
)

Arguments

object

(tern_mmrm)
model result produced by fit_mmrm().

type

(string)
specifying the type of diagnostic plot to be produced:

• fit-residual: A fitted vs residuals plot, grouped by visits. This allows to see if there is remaining structure in the residuals that might be captured by adding additional covariates to the model.

• q-q-residual: A Q-Q plot for the residuals (i.e. sorted standardized residuals vs. normal quantiles), grouped by visits. Observations with an absolute standardized residual above z_threshold will be labeled.

z_threshold

(numeric)
optional number indicating the normal quantile threshold for the Q-Q plot.

Details

Here we use marginal fitted values and residuals. That is, we estimate fitted values, and the difference of those fitted values vs. the observed data are the residuals.

Value

A ggplot2 plot.

See Also

g_mmrm_lsmeans() for plotting the least-squares means and contrasts.

Examples

mmrm_results <- fit_mmrm(
  vars = list(
    response = "FEV1",
    covariates = c("RACE", "SEX"),
    id = "USUBJID",
    arm = "ARMCD",
    visit = "AVISIT"
  ),
  data = mmrm_test_data,
  cor_struct = "unstructured",
  weights_emmeans = "equal"
)
g_mmrm_diagnostic(mmrm_results)
g_mmrm_diagnostic(mmrm_results, type = "q-q-residual")