Two Methods for Calculating Symptom Cluster Scores.

ABSTRACT:

Background

Symptom clusters are conventionally distilled into a single score using composite scoring, which is based on the mathematical assumption that all symptoms are equivalently related to outcomes of interest; this may lead to a loss of important variation in the data.

Objectives

This article compares two ways of calculating a single score for a symptom cluster: a conventional, hypothesis-driven composite score versus a data-driven, reduced rank regression score that weights the symptoms based on their individual relationships with key outcomes.

Methods

We conducted a secondary analysis of psychoneurological symptoms from a sample of 356 low-income mothers. Four of the psychoneurological symptoms (fatigue, cognitive dysfunction, sleep disturbance, and depressed

SUBMITTER: Salomon RE 

PROVIDER: S-EPMC7050366 | biostudies-literature | 2020 Mar/Apr

REPOSITORIES: biostudies-literature