es_from_rr_pval {metaConvert}

Convert a risk ratio value and its p-value to three effect measures (SMD, OR, COR)

Description

Convert a risk ratio value and its p-value to three effect measures (SMD, OR, COR)

Usage

es_from_rr_pval(
  rr,
  logrr,
  rr_pval,
  baseline_risk,
  n_exp,
  n_nexp,
  n_cases,
  n_controls,
  rr_to_or = "metaumbrella",
  smd_to_cor = "viechtbauer",
  reverse_rr_pval
)

Arguments

rr

risk ratio value

logrr

log risk ratio value

rr_pval

p-value of the risk ratio

baseline_risk

proportion of cases in the non-exposed group (only required for the rr_to_or = "grant_CI" and rr_to_or = "grant_2x2" arguments).

n_exp

number of participants in the exposed group (only required for the rr_to_or = "grant_CI", rr_to_or = "grant_2x2" arguments).

n_nexp

number of participants in the non-exposed group (only required for the rr_to_or = "grant_CI", rr_to_or = "grant_2x2" arguments).

n_cases

number of cases/events

n_controls

number of controls/no-event

rr_to_or

formula used to convert the rr value into an odds ratio (see details).

smd_to_cor

formula used to convert the SMD value (converted from RR) into a coefficient correlation (see es_from_cohen_d).

reverse_rr_pval

a logical value indicating whether the direction of the generated effect sizes should be flipped.

Details

This function uses the p-value of the (log) risk ratio to obtain the standard error (Section 6.3.2 in the Cochrane Handbook).

logrr\_z = qnorm(rr_pval/2, lower.tail=FALSE)

logrr\_se = |\frac{\log(rr)}{logrr\_z}|

Then, calculations of es_from_rr_se are applied.

Value

This function estimates and converts between several effect size measures.

natural effect size measure	RR
converted effect size measure	OR + NNT
required input data	See 'Section 3. Risk Ratio'
	https://metaconvert.org/html/input.html

References

Higgins, J. P., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2019). Cochrane handbook for systematic reviews of interventions. John Wiley & Sons.

Examples

es_rr <- es_from_rr_pval(
  rr = 3.51, rr_pval = 0.001,
  n_cases = 12, n_controls = 68
)