Tipping-point sensitivity to a single unmeasured confounder (tipr) — morie_sensitivity_tipping

Thin interface to tipr::tip: returns the minimum value of the standardised mean difference (smd) or partial R-squared (R2) of an unmeasured confounder that would tip the lower (or upper) bound of the confidence interval back to the null. Pairs with tipping_point_analysis, which targets missing-data sensitivity rather than unmeasured-confounder sensitivity.

Usage

morie_sensitivity_tipping_point(estimate, smd = NULL, r2 = NULL, ...)

Arguments

estimate: Observed treatment effect on the coefficient scale.
smd: Hypothesised standardised mean difference of the unmeasured confounder between treatment groups.
r2: Hypothesised partial R-squared of the unmeasured confounder with the outcome. Forwarded as the r_squared tipr argument.
...: Additional arguments forwarded to tipr::tip (e.g. outcome_type, confidence).

Value

A list of class morie_sensitivity_tipping_point with the tipped point estimate and the raw tipr object.

References

D'Agostino McGowan, L. (2022). tipr: An R package for sensitivity analyses for unmeasured confounders. Journal of Open Source Software, 7(77), 4495.

Examples

if (requireNamespace("tipr", quietly = TRUE)) {
  str(morie_sensitivity_tipping_point(0.5, smd = 0.3), max.level = 1)
}
#> ℹ The observed effect (0.5) WOULD be tipped by 1 unmeasured confounder with the
#>   following specifications:
#> • estimated difference in scaled means between the unmeasured confounder in the
#>   exposed population and unexposed population: 0.3
#> • estimated relationship between the unmeasured confounder and the outcome: 0.1
#> List of 6
#>  $ estimate       : num 0.5
#>  $ smd            : num 0.3
#>  $ r2             : NULL
#>  $ tipped_estimate: num 1
#>  $ method         : chr "tip (tipr)"
#>  $ raw            : tibble [1 × 5] (S3: tbl_df/tbl/data.frame)
#>  - attr(*, "class")= chr [1:2] "morie_sensitivity_tipping_point" "list"