fitted {meta4diag}

Get the estimated values of accuracies for each study.

Description

Takes a meta4diag object produced by meta4diag() and returns the estimated study specified accuracies, such as sensitivity, specificity, odds ratios and likelihood ratios for each study.

Usage

## S3 method for class 'meta4diag'
fitted(object, accuracy.type = "sens",...)

Arguments

object

A meta4diag object.

accuracy.type

A string specifying the accuracy type. Options are "sens", "TPR", "spec", "TNR", "FPR", "FNR", "LRpos", "LRneg", "RD", "LLRpos", "LLRneg", "LDOR", and "DOR".

• "sens" and "TPR": The true positive rate, known as sensitivity, sens = \frac{TP}{TP+FN}.

• "spec" and "TNR": The true negative rate, known as specificity, spec = \frac{TN}{TN+FP}.

• "FPR": The false positive rate, FPR = \frac{FP}{FP+TN}.

• "FNR": The false negative rate, FNR = \frac{FN}{FN+TP}.

• "LRpos": The positive likelihood ratio, LRpos = \frac{sens}{1-spec}.

• "LRneg": The negative likelihood ratio, LRneg = \frac{1-sens}{spec}.

• "RD": The risk difference, RD = sens-(1-spec).

• "DOR": The diagnostic odds ratio, DOR = \frac{LRpos}{LRneg}.

• "LLRpos": The log positive likelihood ratio, LLRpos = log(\frac{sens}{1-spec}).

• "LLRneg": The log negative likelihood ratio, LLRneg = log(\frac{1-sens}{spec}).

• "LDOR": The log diagnostic odds ratio, LDOR = log(\frac{LRpos}{LRneg}).

...

Arguments to be passes to methods.

Value

A data frame with the estimated mean, standard deviation and the corresponding quantiles, which are specified by user when the user runs the main function meta4diag(), of the accuracies of each sudy.

Author(s)

Jingyi Guo

Examples

## Not run: 
if(requireNamespace("INLA", quietly = TRUE)){
  require("INLA", quietly = TRUE)
  data(Catheter)
  res <- meta4diag(data = Catheter, nsample=2000)
  fitted(res, accuracy.type="sens")
  fitted(res, accuracy.type="DOR")
}

## End(Not run)