metafor (version 1.9-2)

confint.rma.uni: Compute Confidence Intervals for 'rma' Objects

Description

The function calculates a confidence interval for the amount of (residual) heterogeneity in random- and mixed-effects models that were fitted with the rma.uni function. Confidence intervals for the model coefficients can also be obtained.

Usage

## S3 method for class 'rma.uni':
confint(object, parm, level=object$level, fixed=FALSE, random=TRUE,
        digits=object$digits, verbose=FALSE, control, \dots)
## S3 method for class 'rma.mh':
confint(object, parm, level=object$level, digits=object$digits, \dots)
## S3 method for class 'rma.peto':
confint(object, parm, level=object$level, digits=object$digits, \dots)
## S3 method for class 'rma.glmm':
confint(object, parm, level=object$level, digits=object$digits, \dots)

Arguments

object

an object of class "rma.uni", "rma.mh", or "rma.peto". The method is not yet implemented for objects of class "rma.glmm".

parm

this argument is here for compatability with the generic function confint, but is ignored.

level

numerical value between 0 and 100 specifying the confidence interval level (the default is to take the value from the object).

fixed

logical indicating whether confidence intervals for the model coefficients should be returned (default is FALSE).

random

logical indicating whether a confidence interval for the amount of (residual) heterogeneity should be returned (default is TRUE).

digits

integer specifying the number of decimal places to which the results should be rounded (the default is to take the value from the object).

verbose

logical indicating whether output should be generated on the progress of the iterative algorithm used as part of the Q-profile method (default is FALSE). See Note.

control

list of control values for the iterative algorithm. If unspecified, default values are defined inside the function. See Note.

...

other arguments.

Value

• An object of class "confint.rma". The object is a list with either one or two elements (named fixed and random) with the following elements:
• estimate
  estimate of the model coefficient or variance component.
• ci.lb
  lower bound of the confidence interval.
• ci.ub
  upper bound of the confidence interval.
• For fixed-effects models, the variance component estimates are NA, but the confidence interval bounds are still provided. The results are formated and printed with the print.confint.rma function.

Details

The confidence intervals for the model coefficients are simply the usual Wald-type intervals which are also shown when printing the fitted object. The confidence interval for the amount of (residual) heterogeneity is obtained iteratively via the Q-profile method as described by Hartung and Knapp (2005) and Viechtbauer (2007). The method provides an exact confidence interval for $\tau^2$ in random- and mixed-effects models. The square root of the interval bounds is also returned for easier interpretation. Confidence intervals for $I^2$ and $H^2$ are also provided (Higgins & Thompson, 2002). Since $I^2$ and $H^2$ are just monotonic transformation of $\tau^2$, the confidence intervals for $I^2$ and $H^2$ are also exact.

References

Hartung, J., & Knapp, G. (2005). On confidence intervals for the among-group variance in the one-way random effects model with unequal error variances. Journal of Statistical Planning and Inference, 127, 157--177. Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21, 1539--1558. Mantel, N., & Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the National Cancer Institute, 22, 719--748. Viechtbauer, W. (2007). Confidence intervals for the amount of heterogeneity in meta-analysis. Statistics in Medicine, 26, 37--52. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1--48. http://www.jstatsoft.org/v36/i03/. Yusuf, S., Peto, R., Lewis, J., Collins, R., & Sleight, P. (1985). Beta blockade during and after myocardial infarction: An overview of the randomized trials. Progress in Cardiovascular Disease, 27, 335--371.

See Also

rma.uni, rma.mh, rma.peto

Examples

### load BCG vaccine data
data(dat.bcg)

### meta-analysis of the log relative risks using a random-effects model
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg,
           data=dat.bcg, measure="RR", method="REML")

### confidence interval for the total amount of heterogeneity
confint(res)

### mixed-effects model with absolute latitude in the model
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, mods=ablat,
           data=dat.bcg, measure="RR", method="REML")

### confidence interval for the residual amount of heterogeneity
confint(res)