Bounding the bias limits of unmeasured confounding.

Function to elicit the limits on measures of effect corrected for an unmeasured confounder when only some of the bias parameters are known. Crude relative risk between exposure and outcome has minimally to be provided. Up to 3 other parameters can be entered.

Usage

confounders.limit(p = NA, RR = NA, OR = NA, crude_RR = NULL)

Arguments

p

Proportion with the confounder among the unexposed group.

RR

Relative risk between the confounder and the outcome.

OR

Odds ratio between the confounder and the outcome.

crude_RR

Crude relative risk between the exposure and the outcome.

Value

A list with elements:

model

Bias analysis performed.

bias_parms

Input bias parameters.

adj_measures

Output results.

References

Fox, M.P, MacLehose, R.F., Lash, T.L., 2021 Applying Quantitative Bias Analysis to Epidemiologic Data, pp.129–131, Springer.

Flanders, W. Dana, Khoury, Muin J., 1990. Indirect Assessment of Confounding: Graphic Description and Limits on Effect of Adjusting for Covariates. Epidemiology 1(3): 239–246.

See also

Other confounding: confounders(), confounders.array(), confounders.evalue(), confounders.ext(), probsens.irr.conf()

Examples

confounders.limit(OR = 1.65, crude_RR = 1.5)
#> 
#> ── Input bias parameters ──
#> 
#>                                 
#> p(Confounder+|Exposure-):       
#> RR(Confounder-Disease):         
#> OR(Confounder-Exposure):    1.65
#> Crude RR(Exposure-Disease): 1.50
#> ────────────────────────────────────────────────────────────────────────────────
#>                        Lower bound Upper bound
#> Limits on adjusted RR:   0.9090909   1.5000000