| Title |
Longitudinal beta regression models for analyzing health-related quality of life scores over time
|
|---|---|
| Published in |
BMC Medical Research Methodology, September 2012
|
| DOI | 10.1186/1471-2288-12-144 |
| Pubmed ID | |
| Authors |
Matthias Hunger, Angela Döring, Rolf Holle |
| Abstract |
Health-related quality of life (HRQL) has become an increasingly important outcome parameter in clinical trials and epidemiological research. HRQL scores are typically bounded at both ends of the scale and often highly skewed. Several regression techniques have been proposed to model such data in cross-sectional studies, however, methods applicable in longitudinal research are less well researched. This study examined the use of beta regression models for analyzing longitudinal HRQL data using two empirical examples with distributional features typically encountered in practice. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 115 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 23% |
| Researcher | 19 | 17% |
| Student > Master | 17 | 15% |
| Student > Doctoral Student | 8 | 7% |
| Other | 7 | 6% |
| Other | 15 | 13% |
| Unknown | 23 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 19% |
| Mathematics | 12 | 10% |
| Economics, Econometrics and Finance | 8 | 7% |
| Agricultural and Biological Sciences | 6 | 5% |
| Social Sciences | 5 | 4% |
| Other | 30 | 26% |
| Unknown | 32 | 28% |
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 02 December 2013.
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#18,314,922
of 22,678,224 outputs
Outputs from BMC Medical Research Methodology
#1,727
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Outputs of similar age
#129,769
of 170,681 outputs
Outputs of similar age from BMC Medical Research Methodology
#27
of 33 outputs
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