| Title |
Using an innovative multiple regression procedure in a cancer population (Part II): fever, depressive affect, and mobility problems clarify an influential symptom pair (pain–fatigue/weakness) and cluster (pain–fatigue/weakness–sleep problems)
|
|---|---|
| Published in |
OncoTargets and therapy, December 2014
|
| DOI | 10.2147/ott.s68859 |
| Pubmed ID | |
| Authors |
Richard B Francoeur |
| Abstract |
Most patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. However, only combinations where symptoms are mutually influential hold potential for identifying patient subgroups at greater risk, and in some contexts, interventions with "cross-over" (multisymptom) effects. Improved methods to detect and interpret interactions among symptoms, signs, or biomarkers are needed to reveal these influential pairs and clusters. I recently created sequential residual centering (SRC) to reduce multicollinearity in moderated regression, which enhances sensitivity to detect these interactions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 29 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 19% |
| Student > Ph. D. Student | 5 | 16% |
| Researcher | 3 | 10% |
| Student > Doctoral Student | 3 | 10% |
| Student > Bachelor | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 9 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 32% |
| Nursing and Health Professions | 6 | 19% |
| Psychology | 3 | 10% |
| Computer Science | 1 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2015.
All research outputs
#20,656,161
of 25,373,627 outputs
Outputs from OncoTargets and therapy
#1,597
of 3,016 outputs
Outputs of similar age
#274,278
of 369,133 outputs
Outputs of similar age from OncoTargets and therapy
#15
of 17 outputs
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