Print and summary methods for objects of class "escalc"
.
# S3 method for escalc
print(x, digits, …)# S3 method for escalc
summary(object, out.names=c("sei","zi","ci.lb","ci.ub"), var.names,
H0=0, append=TRUE, replace=TRUE, level=95, digits, transf, …)
an object of class "escalc"
.
an object of class "escalc"
.
integer specifying the number of decimal places to which the printed results should be rounded (the default is to take the value from the object if possible).
character string with four elements, specifying the variable names for the standard errors, test statistics, and lower/upper confidence interval bounds.
character string with two elements, specifying the variable names for the observed outcomes and the sampling variances (the default is to take the value from the object if possible).
numeric value specifying the value of the outcome under the null hypothesis.
logical indicating whether the data frame specified via the object
argument should be returned together with the additional variables that are calculated by the summary
function (the default is TRUE
).
logical indicating whether existing values for sei
, zi
, ci.lb
, and ci.ub
in the data frame should be replaced or not. Only relevant when the data frame already contains these variables. If replace=TRUE
(the default), all of the existing values will be overwritten. If replace=FALSE
, only NA
values will be replaced.
numerical value between 0 and 100 specifying the confidence interval level (the default is 95).
optional argument specifying the name of a function that should be used to transform the observed outcomes and interval bounds (e.g., transf=exp
; see also transf). If unspecified, no transformation is used. Any additional arguments needed for the function specified here can be passed via …
.
other arguments.
The print.escalc
function formats and prints the data frame, so that the observed outcomes and sampling variances are rounded (to the number of digits specified).
The summary.escalc
function creates an object that is a data frame containing the original data (if append=TRUE
) and the following components:
observed outcomes or effect size estimates (transformed if transf
is specified).
corresponding (estimated) sampling variances.
standard errors of the observed outcomes or effect size estimates.
test statistics for testing \(H<U+2080>: \theta<U+1D62> = H0\) (i.e., (yi-H0)/sei
).
lower confidence interval bounds (transformed if transf
is specified).
upper confidence interval bounds (transformed if transf
is specified).
Note that the actual variable names above depend on the out.names (and var.names) arguments. If the data frame already contains variables with names as specified by the out.names argument, the values for these variables will be overwritten when replace=TRUE (which is the default). By setting replace=FALSE, only values that are NA will be replaced.
The print.escalc function again formats and prints the data frame, rounding the added variables to the number of digits specified.
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/.
# NOT RUN {
### calculate log risk ratios and corresponding sampling variances
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
dat
### apply summary function
summary(dat)
summary(dat, transf=exp)
# }
Run the code above in your browser using DataCamp Workspace