vcmeta (version 1.5.0)

meta.lm.agree: Meta-regression analysis for G agreement indices

Description

This function estimates the intercept and slope coefficients in a meta-regression model where the dependent variable is a G-index of agreement. The estimates are OLS estimates with robust standard errors that accomodate residual heteroscedasticity.

Usage

meta.lm.agree(alpha, f11, f12, f21, f22, X)

Value

Returns a matrix. The first row is for the intercept with one additional row per predictor. The matrix has the following columns:

• Estimate - OLS estimate

• SE - standard error

• z - z-value

• p - p-value

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

Arguments

alpha

alpha level for 1-alpha confidence

f11

vector of frequency counts in cell 1,1

f12

vector of frequency counts in cell 1,2

f21

vector of frequency counts in cell 2,1

f22

vector of frequency counts in cell 2,2

X

matrix of predictor values

References

Bonett2022vcmeta

Examples

f11 <- c(40, 20, 25, 30)
f12 <- c(3, 2, 2, 1)
f21 <- c(7, 6, 8, 6)
f22 <- c(26, 25, 13, 25)
x1 <- c(1, 1, 4, 6)
x2 <- c(1, 1, 0, 0)
X <- matrix(cbind(x1, x2), 4, 2)
meta.lm.agree(.05, f11, f12, f21, f22, X)

# Should return:
#     Estimate         SE         z     p          LL        UL
# b0 0.1904762 0.38772858 0.4912617 0.623 -0.56945786 0.9504102
# b1 0.0952381 0.07141957 1.3335013 0.182 -0.04474169 0.2352179
# b2 0.4205147 0.32383556 1.2985438 0.194 -0.21419136 1.0552207