Abstract
BACKGROUND. Current analytic methods applied to multidimensional health-related quality of life (HRQOL) data do not borrow strength across analyses and do not produce summary estimates of effect. OBJECTIVES. To compare a random effects modelling approach for the analysis of multidimensional HRQOL data to the following: (1) separate analyses for each dimension; (2) O'Brien's global test procedure; and (3) multivariate analysis of variance (MANOVA). RESEARCH DESIGN. Randomized clinical trial comparing 3 treatments (Trimethoprim-Sulfamethoxazole [TS], Dapsone-Trimethoprim [DT], and Clindamycin-Primaquine [CP] for Pneumocystis carinii pneumonia [PCP]). SUBJECTS. Patients with PCP enrolled in AIDS Clinical Trials Group Protocol 108. MEASURES. A 33-item battery assessing 7 dimensions of HRQOL: physical functioning, pain, energy, general health perceptions, disability, pulmonary symptoms, and constitutional symptoms. RESULTS. Analyses focused on changes in score from baseline to Day 7 (n = 145). Separate analyses for each dimension suggested a trend favoring CP versus TS, but using a Bonferroni correction no differences were statistically significant. O'Brien's global procedure for a test of no-treatment effect versus superiority of one treatment yielded P = 0.07. MANOVA did not reveal significant differences among treatment groups. A random effects model using fixed treatment and dimension effects and separate random effects for each person showed a significant overall treatment effect (P = 0.02); changes in scores for CP averaged 10 points greater than for TS. CONCLUSIONS. Random-effects models provide a flexible class of models for analyzing multidimensional quality of life data and estimating treatment effects because they borrow strength across dimensions.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 249-258 |
| Number of pages | 10 |
| Journal | Medical Care |
| Volume | 37 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 1999 |
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Keywords
- Analytic methods
- Clinical trial
- HIV/AIDS
- Quality of life
- Random effects
ASJC Scopus subject areas
- Nursing(all)
- Public Health, Environmental and Occupational Health
- Health(social science)
- Health Professions(all)
Cite this
Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial. / Wu, Albert W; Gray, Sarah M.; Brookmeyer, Ronald.
In: Medical Care, Vol. 37, No. 3, 03.1999, p. 249-258.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial
AU - Wu, Albert W
AU - Gray, Sarah M.
AU - Brookmeyer, Ronald
PY - 1999/3
Y1 - 1999/3
N2 - BACKGROUND. Current analytic methods applied to multidimensional health-related quality of life (HRQOL) data do not borrow strength across analyses and do not produce summary estimates of effect. OBJECTIVES. To compare a random effects modelling approach for the analysis of multidimensional HRQOL data to the following: (1) separate analyses for each dimension; (2) O'Brien's global test procedure; and (3) multivariate analysis of variance (MANOVA). RESEARCH DESIGN. Randomized clinical trial comparing 3 treatments (Trimethoprim-Sulfamethoxazole [TS], Dapsone-Trimethoprim [DT], and Clindamycin-Primaquine [CP] for Pneumocystis carinii pneumonia [PCP]). SUBJECTS. Patients with PCP enrolled in AIDS Clinical Trials Group Protocol 108. MEASURES. A 33-item battery assessing 7 dimensions of HRQOL: physical functioning, pain, energy, general health perceptions, disability, pulmonary symptoms, and constitutional symptoms. RESULTS. Analyses focused on changes in score from baseline to Day 7 (n = 145). Separate analyses for each dimension suggested a trend favoring CP versus TS, but using a Bonferroni correction no differences were statistically significant. O'Brien's global procedure for a test of no-treatment effect versus superiority of one treatment yielded P = 0.07. MANOVA did not reveal significant differences among treatment groups. A random effects model using fixed treatment and dimension effects and separate random effects for each person showed a significant overall treatment effect (P = 0.02); changes in scores for CP averaged 10 points greater than for TS. CONCLUSIONS. Random-effects models provide a flexible class of models for analyzing multidimensional quality of life data and estimating treatment effects because they borrow strength across dimensions.
AB - BACKGROUND. Current analytic methods applied to multidimensional health-related quality of life (HRQOL) data do not borrow strength across analyses and do not produce summary estimates of effect. OBJECTIVES. To compare a random effects modelling approach for the analysis of multidimensional HRQOL data to the following: (1) separate analyses for each dimension; (2) O'Brien's global test procedure; and (3) multivariate analysis of variance (MANOVA). RESEARCH DESIGN. Randomized clinical trial comparing 3 treatments (Trimethoprim-Sulfamethoxazole [TS], Dapsone-Trimethoprim [DT], and Clindamycin-Primaquine [CP] for Pneumocystis carinii pneumonia [PCP]). SUBJECTS. Patients with PCP enrolled in AIDS Clinical Trials Group Protocol 108. MEASURES. A 33-item battery assessing 7 dimensions of HRQOL: physical functioning, pain, energy, general health perceptions, disability, pulmonary symptoms, and constitutional symptoms. RESULTS. Analyses focused on changes in score from baseline to Day 7 (n = 145). Separate analyses for each dimension suggested a trend favoring CP versus TS, but using a Bonferroni correction no differences were statistically significant. O'Brien's global procedure for a test of no-treatment effect versus superiority of one treatment yielded P = 0.07. MANOVA did not reveal significant differences among treatment groups. A random effects model using fixed treatment and dimension effects and separate random effects for each person showed a significant overall treatment effect (P = 0.02); changes in scores for CP averaged 10 points greater than for TS. CONCLUSIONS. Random-effects models provide a flexible class of models for analyzing multidimensional quality of life data and estimating treatment effects because they borrow strength across dimensions.
KW - Analytic methods
KW - Clinical trial
KW - HIV/AIDS
KW - Quality of life
KW - Random effects
UR - http://www.scopus.com/inward/record.url?scp=0033087773&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0033087773&partnerID=8YFLogxK
U2 - 10.1097/00005650-199903000-00005
DO - 10.1097/00005650-199903000-00005
M3 - Article
VL - 37
SP - 249
EP - 258
JO - Medical Care
JF - Medical Care
SN - 0025-7079
IS - 3
ER -