| meta.lm.agree {vcmeta} | R Documentation |
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)
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 |
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
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