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Confidence interval for a log-linear contrast of proportion ratios from 2-group studies

Source: R/meta_comp.R
meta.lc.propratio2.Rd

Computes the estimate, standard error, and confidence interval for an exponentiated log-linear contrast of 2-group proportion ratios from two or more studies.

For more details, see Section 3.2 of Bonett (2021, Volume 5).

Usage

meta.lc.propratio2(alpha, f1, f2, n1, n2, v)

Arguments

alpha

alpha level for 1-alpha confidence

f1

vector of group 1 frequency counts

f2

vector of group 2 frequency counts

n1

vector of group 1 sample sizes

n2

vector of group 2 sample sizes

v

vector of contrast coefficients

Value

Returns 1-row matrix with the following columns:

  • Estimate - estimated log-linear contrast

  • SE - standard error of log-linear contrast

  • exp(Estimate) - exponentiated log-linear contrast

  • exp(LL) - lower limit of the exponentiated confidence interval

  • exp(UL) - upper limit of the exponentiated confidence interval

References

Price RM, Bonett DG (2008). “Confidence intervals for a ratio of two independent binomial proportions.” Statistics in Medicine, 27(26), 5497–5508. ISSN 02776715, doi:10.1002/sim.3376 .

Bonett DG, Price RM (2015). “Varying coefficient meta-analysis methods for odds ratios and risk ratios.” Psychological Methods, 20(3), 394–406. ISSN 1939-1463, doi:10.1037/met0000032 .

Bonett DG (2021). Statistical Methods for Psychologists, Vol 1-5, https://dgbonett.sites.ucsc.edu/.

Examples

n1 <- c(50, 150, 150)
f1 <- c(16, 50, 25)
n2 <- c(50, 150, 150)
f2 <- c(7, 15, 20)
v <- c(1, -1, 0)
meta.lc.propratio2(.05, f1, f2, n1, n2, v)
#>            Estimate        SE exp(Estimate)   exp(LL)  exp(UL)
#> Contrast -0.3853396 0.4828218     0.6802196 0.2640405 1.752378

# Should return:
#            Estimate        SE  exp(Estimate)   exp(LL)  exp(UL)
# Contrast -0.3853396 0.4828218      0.6802196 0.2640405 1.752378