Indirect method for the estimation of reference intervals using Real-World Data ('RWD'). It takes routine measurements
of diagnostic tests, containing pathological and non-pathological samples as input and uses sophisticated
statistical methods to derive a model describing the distribution of the non-pathological samples. This distribution can then be
used to derive reference intervals.
Furthermore, the package offers functions for printing and plotting the results of the algorithm. See ?refineR for a more comprehensive description of the features.
Version 1.0 of the algorithm is described in detail in Ammer T., Schuetzenmeister A., Prokosch H.-U., Rauh M., Rank C.M., Zierk J. "refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data". Scientific Reports (2021) <doi:10.1038/s41598-021-95301-2>.

Cluster and Merge Similar Values Within a Character Vector
These functions take a character vector as input, identify and cluster similar values, and then merge clusters together so their values become identical. The functions are an implementation of the key collision and ngram fingerprint algorithms from the open source tool Open Refine <http://openrefine.org/>. More info on key collision and ngram fingerprint can be found here <https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth>.

These functions take a character vector as input, identify and
cluster similar values, and then merge clusters together so their values
become identical. The functions are an implementation of the key collision
and ngram fingerprint algorithms from the open source tool Open Refine
<http://openrefine.org/>. More info on key collision and ngram fingerprint
can be found here <https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth>.

These functions take a character vector as input, identify and
cluster similar values, and then merge clusters together so their values
become identical. The functions are an implementation of the key collision
and ngram fingerprint algorithms from the open source tool Open Refine
<https://openrefine.org/>. More info on key collision and ngram fingerprint
can be found here <https://docs.openrefine.org/next/technical-reference/clustering-in-depth/>.