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Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial.

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Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial. / Wu, A. W.; Gray, S. M.; Brookmeyer, R.
In: Medical Care, Vol. 37, No. 3, 03.1999, p. 249-258.

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Wu, A. W. ; Gray, S. M. ; Brookmeyer, R. / Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial. In: Medical Care. 1999 ; Vol. 37, No. 3. pp. 249-258.

Bibtex

@article{cd48b40334bb4fe4a578a34bf84c5df8,
title = "Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial.",
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.",
author = "Wu, {A. W.} and Gray, {S. M.} and R. Brookmeyer",
year = "1999",
month = mar,
language = "English",
volume = "37",
pages = "249--258",
journal = "Medical Care",
issn = "1537-1948",
publisher = "Lippincott Williams and Wilkins",
number = "3",

}

RIS

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, A. W.

AU - Gray, S. M.

AU - Brookmeyer, R.

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.

M3 - Journal article

VL - 37

SP - 249

EP - 258

JO - Medical Care

JF - Medical Care

SN - 1537-1948

IS - 3

ER -