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Optimization of Sensitivity and Specificity

dot-get_values.Rd

Determine final optimized values for the sensitivity and specificity of an experimental test kit (and probability of suspect given disease positive and given disease negative for a 3-state kit).

Usage

.get_values(
  dat,
  SnR.vec,
  SpR.vec,
  prev.vec,
  N.vec,
  nstates,
  tolerance,
  rep.iter,
  iter.n,
  parm = NULL
)

Arguments

dat

vector A vector of counts ordered in a manner consistent with output from the .cell_counts function.

SnR.vec

data.frame Each column corresponds to one reference test. Row 1 contains the sensitivity for the reference test(s). Row 2 contains the probability of a suspect result as a fraction of the non-correct test result. This is a value between 0 and 1 (inclusive). Namely, P(T? | D+) = \(\psi\) = \(\delta\) * (1 - \(\pi\)) where \(\delta\) is the second row for a given column (reference test). \(\delta = \frac{\psi}{(1 - \pi)}\). Use a zero for a 2-state test (i.e. no suspect region).

SpR.vec

data.frame Each column corresponds to one reference test. Row 1 contains the specificity for each reference test. Row 2 contains the probability of a suspect result as a fraction of the non-correct test result. This is a value between 0 and 1 (inclusive). Namely, P(T? | D-) = \(\phi\) = \(\gamma\) * (1 - \(\theta\)) where \(\gamma\) is the second row for a given column (reference test). \(\gamma = \frac{\phi}{(1 - \theta)}\). Use a zero for a 2-state test (i.e. no suspect region).

prev.vec

vector A named vector containing the prevalence for each population sampled.

N.vec

vector A named vector containing the sample size for each population sampled.

nstates

vector A vector with length one more than the number of reference tests. The first element is the number of states of the experimental test and the remaining entries are the number of states of each reference test (using the same ordering as SnR.vec and SpR.vec).

tolerance

Setting a limit on the pgtol used in the optim function with the "L-BFGS-B" method. See also optim.

rep.iter

logical (TRUE/FALSE) Indicates if updates should be printed regarding the number of iterations completed.

iter.n

integer indicating the frequency of updates for the number of iterations completed.

parm

vector A vector of starting values to be used for the optimization that is passed to .minimize_cell. For a 2-state experimental test, this is a vector of length 2 with entries (\(\pi\), \(\theta\)). For a 3-state experimental test, this is a vector of length 4 with entries (\(\pi\), \(\delta\), \(\theta\), \(\gamma\)). See also estimateSnSp.

Value

A list:

The following will be returned for both 2 and 3-state experimental tests –

  • sens.final: vector The optimized values for the sensitivity of the experimental test kit.

  • spec.final: vector The optimized values for the specificity of the experimental test kit.

  • converge: vector Each entry is an integer code detailing the convergence of the optimization for each iteration. 0 indicates successful completion. See also optim.

  • message: vector Each entry includes a character string giving any additional information returned by the optimizer or NULL. See also optim.

If three states –

  • \(\delta\): vector The optimized values for the probability of a suspect result as a fraction of the non-correct test result for diseased samples.

  • \(\gamma\): vector The optimized value for the probability of a suspect result as a fraction of the non-correct test result for non-diseased samples.

Author

DiagTestKit-package