quint-package: R package for Qualitative Treatment-Subgroup Interactions

In quint: Qualitative Interaction Trees

R package for Qualitative Treatment-Subgroup Interactions

Description

When two treatment alternatives (say A and B) are available for some problem, one may be interested in qualitative treatment-subgroup interactions. Such interactions imply the existence of subgroups of persons (patients) which are such that in one subgroup Treatment A outperforms Treatment B, whereas the reverse holds in another subgroup. Obviously, this type of interactions is crucial for optimal treatment assignment of future patients. Given baseline characteristics and outcome data from a two-arm Randomized Controlled Trial (RCT), QUalitative INteraction Trees (QUINT) is a tool to identify subgroups that are involved in meaningful qualitative treatment-subgroup interactions. The result of QUINT is a tree that partitions the total group of participants (patients) on the basis of their baseline characteristics into three subgroups (i.e., partition classes): Subgroup 1: Those for whom Treatment A is better than Treatment B (P1), Subgroup 2: Those for whom Treatment B is better than Treatment A (P2), and Subgroup 3: Those for whom it does not make any difference (P3).

Details

Package:	quint
Type:	Package
Version:	2.2.0
Date:	2020-02-03
License:	GPL

This method is suitable for a continuous outcome variable. From version 1.2 onwards the baseline variables for growing a tree may have numerical or integer values (such as continuous, ordinal or dichotomous variables) or may be nominal (categorical variables with factors). Previously only numerical or dichotomous variables were supported. Another new feature of this version is that the output of a quint object can now also display results for either the raw difference in means or the effect size with corresponding standard error. This depends on the criterion specified. Furthermore a predict function predict.quint is newly included in this package. The final new feature is a validate function quint.validate for estimating the bias (i.e., optimism) of a grown QUINT tree.

From version 2.0 onwards the qualitative treatment-subgroup interaction is checked during the prune of the tree and not at the begining of QUINT. Furthermore, it is possible to obtain outcomes from the summary and predict functions when the tree only contains the root node.

The core function of the package is quint.

Author(s)

Maintainer: Elise Dusseldorp <[e-mail]>

References

Dusseldorp, E., Doove, L., & Van Mechelen, I. (2016). Quint: An R package for the identification of subgroups of clients who differ in which treatment alternative is best for them. Behavior Research Methods, 48(2), 650-663. DOI 10.3758/s13428-015-0594-z

Dusseldorp E. and Van Mechelen I. (2014). Qualitative interaction trees: a tool to identify qualitative treatment-subgroup interactions. Statistics in Medicine, 33(2), 219-237. DOI: 10.1002/sim.5933.

Scheier M.F., Helgeson V.S., Schulz R., et al.(2007). Moderators of interventions designed to enhance physical and psychological functioning among younger women with early-stage breast cancer. Journal of Clinical Oncology, 25, 5710-5714. DOI: 10.1200/JCO.2007.11.7093.

See Also

quint,summary.quint,quint.control, prune.quint,predict.quint,quint.validate, quint.bootstrapCI

quint documentation built on July 2, 2022, 1:07 a.m.