meta.lm.mean1 {vcmeta}

Meta-regression analysis for 1-group means

Description

This function estimates the intercept and slope coefficients in a meta-regression model where the dependent variable is a mean from one group. The estimates are OLS estimates with robust standard errors that accomodate residual heteroscedasticity.

Usage

meta.lm.mean1(alpha, m, sd, n, X)

Arguments

alpha

alpha level for 1-alpha confidence

m

vector of estimated means

sd

vector of estimated standard deviations

n

vector of sample sizes

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

• t - t-value

• p - p-value

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

• df - degrees of freedom

Examples

n <- c(25, 15, 30, 25, 40)
m <- c(20.1, 20.5, 19.3, 21.5, 19.4)
sd <- c(10.4, 10.2, 8.5, 10.3, 7.8)
x1 <- c(1, 1, 0, 0, 0)
x2 <- c( 12, 13, 11, 13, 15)
X <- matrix(cbind(x1, x2), 5, 2)
meta.lm.mean1(.05, m, sd, n, X)

# Should return: 
#       Estimate        SE          t     p         LL        UL  df
# b0 19.45490196 6.7873381 2.86635227 0.005  6.0288763 32.880928 132
# b1  0.25686275 1.9834765 0.12950128 0.897 -3.6666499  4.180375 132
# b2  0.04705882 0.5064693 0.09291544 0.926 -0.9547876  1.048905 132