metafor (version 1.4-0)

confint.rma.uni: Confidence Intervals for rma.uni 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, control=list(), ...)

Arguments

object

an object of class "rma.uni".

parm

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

level

a 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

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

control

a list of control values for the iterative algorithm. Defaults to an empty list, which means that default values are defined inside the function. See Note.

...

other arguments.

Value

• Either a single data frame or a list with two data frames (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.

Details

The confidence intervals for the model coefficients are simply the usual Wald-type intervals which are also shown when printing the fitted object or when calling coef.rma. 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. For random-effects models, 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. 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/.

See Also

rma.uni

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)