svalues.HR: Compute selection bias E-value for an estimate and its...

In EValue: Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses

Description

Returns a data frame containing point estimates, the lower confidence limit, and the upper confidence limit on the risk ratio scale (through an approximate conversion if needed when outcome is common) as well as selection bias E-values for the point estimate and the confidence interval limit closer to the null.

Usage

svalues.HR(
  est,
  lo = NA,
  hi = NA,
  rare = NA,
  true = 1,
  sel_pop = FALSE,
  S_eq_U = FALSE,
  risk_inc = FALSE,
  risk_dec = FALSE,
  ...
)

Arguments

est	The point estimate
lo	The lower limit of the confidence interval
hi	The upper limit of the confidence interval
rare	1 if outcome is rare (<15 percent at end of follow-up); 0 if outcome is not rare (>15 percent at end of follow-up)
true	The true HR to which to shift the observed point estimate. Typically set to 1 to consider a null true effect.
sel_pop	Whether inference is specific to selected population (TRUE) or entire population (FALSE). Defaults to FALSE.
S_eq_U	Whether the unmeasured factor is assumed to be a defining characteristic of the selected population. Defaults to FALSE.
risk_inc	Whether selection is assumed to be associated with increased risk of the outcome in both exposure groups. Defaults to FALSE.
risk_dec	Whether selection is assumed to be associated with decreased risk of the outcome in both exposure groups. Defaults to FALSE.
...	Arguments passed to other methods.

Details

A selection bias E-value is a summary measure that helps assess susceptibility of a result to selection bias. Each of one or more parameters characterizing the extent of the bias must be greater than or equal to this value to be sufficient to shift an estimate (est) to the null or other true value (true). The parameters, as defined in Smith and VanderWeele 2019, depend on assumptions an investigator is willing to make (see arguments sel_pop, S_eq_U, risk_inc, risk_dec). The svalues.XX functions print a message about which parameters the selection bias E-value refers to given the assumptions made. See the cited article for details.

Examples

# Examples from Smith and VanderWeele 2019

# Obesity paradox example
svalues.RR(est = 1.50, lo = 1.22, sel_pop = TRUE)

Example output

This selection bias E-value refers to RR_UY|S=1 and RR_AU|S=1 (see
documentation)
                           point    lower upper
RR                      1.500000 1.220000    NA
Selection bias E-values 2.366025 1.738073    NA

EValue documentation built on Oct. 28, 2021, 9:10 a.m.