meta.lm.gen: Meta-regression analysis for any type of effect size

In dgbonett/vcmeta: Varying Coefficient Meta-Analysis

Meta-regression analysis for any type of effect size

Description

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

Usage

meta.lm.gen(alpha, est, se, X)

Arguments

alpha	alpha level for 1-alpha confidence
est	vector of parameter estimates
se	vector of standard errors
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

est <- c(4.1, 4.7, 4.9, 5.7, 6.6, 7.3)
se <- c(1.2, 1.5, 1.3, 1.8, 2.0, 2.6)
x1 <- c(10, 20, 30, 40, 50, 60)
x2 <- c(1, 1, 1, 0, 0, 0)
X <- matrix(cbind(x1, x2), 6, 2)
meta.lm.gen(.05, est, se, X)

# Should return:
#      Estimate         SE           z     p         LL         UL
# b0  3.5333333 4.37468253  0.80767766 0.419 -5.0408869 12.1075535
# b1  0.0600000 0.09058835  0.66233679 0.508 -0.1175499  0.2375499
# b2 -0.1666667 2.81139793 -0.05928249 0.953 -5.6769054  5.3435720

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