meta.lc.meanratio.ps: Confidence interval for a log-linear contrast of mean ratios...

In dgbonett/vcmeta: Varying Coefficient Meta-Analysis

Confidence interval for a log-linear contrast of mean ratios from paired-samples studies

Description

Computes the estimate, standard error, and confidence interval for a log-linear contrast of paired-sample mean ratios from two or more studies. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence interval. Equality of variances within or across studies is not assumed.

Usage

meta.lc.meanratio.ps(alpha, m1, m2, sd1, sd2, cor, n, v)

Arguments

alpha	alpha level for 1-alpha confidence
m1	vector of estimated means for measurement 1
m2	vector of estimated means for measurement 2
sd1	vector of estimated SDs for measurement 1
sd2	vector of estimated SDs for measurement 2
cor	vector of estimated correlations for paired measurements
n	vector of sample sizes
v	vector of contrast coefficients

Value

Returns 1-row matrix with the following columns:

• Estimate - estimatedf log-linear contrast

• SE - standard error of log-linear contrast

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

• exp(Estimate) - exponentiated log-linear contrast

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

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

• df - degrees of freedom

References

\insertRef

Bonett2020vcmeta

Examples

m1 <- c(53, 60, 53, 57)
m2 <- c(55, 62, 58, 61)
sd1 <- c(4.1, 4.2, 4.5, 4.0)
sd2 <- c(4.2, 4.7, 4.9, 4.8)
cor <- c(.7, .7, .8, .85)
n <- c(30, 50, 30, 70)
v <- c(.5, .5, -.5, -.5)
meta.lc.meanratio.ps(.05, m1, m2, sd1, sd2, cor, n, v)

# Should return:
#           Estimate          SE         LL         UL exp(Estimate)
# Contrast 0.0440713 0.008701725 0.02681353 0.06132907      1.045057
#           exp(LL)  exp(UL)       df
# Contrast 1.027176 1.063249 103.0256

dgbonett/vcmeta documentation built on July 12, 2024, 3:12 p.m.