summary.statcheck <- structure(function(# Summary method for \code{statcheck}.
### Gives the summaries for a \code{statcheck} object.
object,
### a \code{statcheck} object.
...
### additional arguments affecting the summary produced.
){
##seealso<<
## \code{\link{statcheck}}
x <- object
# Source
Source <- c(ddply(x,"Source",function(x) unique(x$Source))[,2],"Total")
# Number of p values extracted per article and in total
pValues <- c(ddply(x,"Source",function(x) nrow(x))[,2],nrow(x))
# Number of errors per article and in total
Errors <- c(ddply(x,"Source",function(x) sum(x$Error,na.rm=TRUE))[,2],sum(x$Error,na.rm=TRUE))
# Number of decision errors per article and in total
DecisionErrors <- c(ddply(x,"Source",function(x) sum(x$DecisionError,na.rm=TRUE))[,2],sum(x$DecisionError,na.rm=TRUE))
# Results in dataframe
res <- data.frame(Source=c(unique(x$Source),"Total"),
pValues=pValues,
Errors=Errors,
DecisionErrors=DecisionErrors)
class(res) <- c("statcheck","data.frame")
return(res)
##value<<
## A data frame containing for each extracted statistic:
## \item{Source}{Name of the file of which the statistic is extracted}
## \item{pValues}{The number of reported p values per article}
## \item{Errors}{The number of errors per article}
## \item{DecisionErrors}{The number of errors that caused a non-significant result to be reported as significant (or vice versa) per article}
},ex=function(){
Text <- "blablabla the effect was very significant (t(100)=1, p < 0.001)"
Stat <- statcheck(Text)
summary(Stat)
})
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