pimeta (version 1.1.1)

pima_hts: Higgins--Thompson--Spiegelhalter prediction interval

Description

A subroutine for the Higgins--Thompson--Spiegelhalter PI based on the DerSimonian-Laird estimator (Higgins et al., 2009)

Usage

pima_hts(y, sigma, alpha = 0.05)

Arguments

y

the effect size estimates vector

sigma

the within studies standard errors vector

alpha

the alpha level of the prediction interval

Value

• muhat: the average treatment effect estimate \(\hat{\mu}\).

• lci, lci: the lower and upper confidence limits \(\hat{\mu}_l\) and \(\hat{\mu}_u\).

• lpi, lpi: the lower and upper prediction limits \(\hat{c}_l\) and \(\hat{c}_u\).

• tau2h: the estimate for \(\tau^2\).

References

Higgins, J. P. T, Thompson, S. G., Spiegelhalter, D. J. (2009). A re-evaluation of random-effects meta-analysis. J R Stat Soc Ser A Stat Soc. 172(1): 137-159.

See Also

pima().

Examples

# NOT RUN {
data(sbp, package = "pimeta")
pimeta::pima_hts(sbp$y, sbp$sigmak)
# 
# Prediction Interval for Random-Effects Meta-Analysis
# 
# Higgins-Thompson-Spiegelhalter prediction interval
#  Heterogeneity variance: DerSimonian-Laird
#  SE for average treatment effect: standard
# 
# Average treatment effect [95%PI]:
#  -0.3341 [-0.7598, 0.0917]
# 
# Average treatment effect [95%CI]:
#  -0.3341 [-0.5068, -0.1613]
# 
# Heterogeneity variance (tau^2):
#  0.0282
# 
# }