The Experts below are selected from a list of 270 Experts worldwide ranked by ideXlab platform
Charles B Eaton - One of the best experts on this subject based on the ideXlab platform.
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Intraclass Correlation coefficients for cluster randomized trials in primary care the cholesterol education and research trial ceart
Contemporary Clinical Trials, 2005Co-Authors: Donna R Parker, Evangelos Evangelou, Charles B EatonAbstract:Cluster randomization trials are increasingly being used in primary care research. The main feature of these trials is that patients are nested within large clusters such as physician practices or communities and the intervention is applied to the cluster. This study design necessitates calculation of Intraclass Correlation coefficients in order to determine the required sample size. The purpose of this study is to determine Intraclass Correlation coefficients for a number of outcome measures at the primary care practice level. The CEART study is a randomized trial testing the effectiveness of translating ATP III guidelines into clinical practice, with primary care physician practices as the unit of randomization and patients as the unit of data collection. The Intraclass Correlation coefficient (ICC) was<0.02 and the design effect ranged from 1.0 to 2.3, respectively, for weight, total cholesterol, LDL, non-HDL, glucose, creatinine, and % at non-HDL goal. For smoking status, body mass index, systolic blood pressure, HDL cholesterol triglycerides, total cholesterol/HDL ratio and % at LDL goal, the ICC was 0.02–0.047 and the design effect was 2.6–4.1. The largest ICCs (0.05–0.12) and design effects (4.4–9.4) were found for height and diastolic blood pressure. These findings suggest that cluster randomization may substantially increase the sample size necessary to maintain adequate statistical power for selected outcomes such as diastolic blood pressure studies compared with simple randomization for most outcomes evaluated in this study where the design effect is small to moderate. Overall, the ICCs presented will be useful in calculating sample sizes at the primary care level.
Terry L Conway - One of the best experts on this subject based on the ideXlab platform.
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school level Intraclass Correlation for physical activity in sixth grade girls
Medicine and Science in Sports and Exercise, 2006Co-Authors: David M Murray, Diane J Catellier, Peter J Hannan, June Stevens, Kathryn H Schmitz, Janet C Rice, Terry L Conway, Marsha Dowda, Song YangAbstract:ABSTRACTPurpose:The Trial for Activity in Adolescent Girls (TAAG) is a group-randomized trial (GRT) to reduce the usual decline in moderate to vigorous physical activity (MVPA) among middle school girls. We report the school-level Intraclass Correlation (ICC) for MVPA from the TAAG baseline survey o
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school level Intraclass Correlation for physical activity in adolescent girls
Medicine and Science in Sports and Exercise, 2004Co-Authors: David M Murray, Diane J Catellier, Peter J Hannan, Margarita S Treuth, June Stevens, Kathryn H Schmitz, Janet C Rice, Terry L ConwayAbstract:ABSTRACTMURRAY, D. M., D. J. CATELLIER, P. J. HANNAN, M. S. TREUTH, J. STEVENS, K. H. SCHMITZ, J. C. RICE, and T. L. CONWAY. School-Level Intraclass Correlation for Physical Activity in Adolescent Girls. Med. Sci. Sports Exerc., Vol. 36, No. 5, pp. 876–882, 2004.Purpose:The Trial for Activity in Ado
David M Murray - One of the best experts on this subject based on the ideXlab platform.
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school level Intraclass Correlation for physical activity in sixth grade girls
Medicine and Science in Sports and Exercise, 2006Co-Authors: David M Murray, Diane J Catellier, Peter J Hannan, June Stevens, Kathryn H Schmitz, Janet C Rice, Terry L Conway, Marsha Dowda, Song YangAbstract:ABSTRACTPurpose:The Trial for Activity in Adolescent Girls (TAAG) is a group-randomized trial (GRT) to reduce the usual decline in moderate to vigorous physical activity (MVPA) among middle school girls. We report the school-level Intraclass Correlation (ICC) for MVPA from the TAAG baseline survey o
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school level Intraclass Correlation for physical activity in adolescent girls
Medicine and Science in Sports and Exercise, 2004Co-Authors: David M Murray, Diane J Catellier, Peter J Hannan, Margarita S Treuth, June Stevens, Kathryn H Schmitz, Janet C Rice, Terry L ConwayAbstract:ABSTRACTMURRAY, D. M., D. J. CATELLIER, P. J. HANNAN, M. S. TREUTH, J. STEVENS, K. H. SCHMITZ, J. C. RICE, and T. L. CONWAY. School-Level Intraclass Correlation for Physical Activity in Adolescent Girls. Med. Sci. Sports Exerc., Vol. 36, No. 5, pp. 876–882, 2004.Purpose:The Trial for Activity in Ado
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methods to reduce the impact of Intraclass Correlation in group randomized trials
Evaluation Review, 2003Co-Authors: David M Murray, Jonathan L BlitsteinAbstract:This study reports Intraclass Correlation (ICC) for dependent variables used in group-randomized trials (GRTs). The authors also document the effect of two methods suggested to reduce the impact of ICC in GRTs; these two methods are modeling time and regression adjustment for covariates. They coded and analyzed 1,188 ICC estimates from 17 published, in press, and unpublished articles representing 21 studies. Findings confirm that both methods can improve the efficiency of analyses shown to be valid across conditions common in GRTs. Investigators planning GRTs should obtain ICC estimates matched to their planned analysis so that they can size their studies properly.
Donna R Parker - One of the best experts on this subject based on the ideXlab platform.
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Intraclass Correlation coefficients for cluster randomized trials in primary care the cholesterol education and research trial ceart
Contemporary Clinical Trials, 2005Co-Authors: Donna R Parker, Evangelos Evangelou, Charles B EatonAbstract:Cluster randomization trials are increasingly being used in primary care research. The main feature of these trials is that patients are nested within large clusters such as physician practices or communities and the intervention is applied to the cluster. This study design necessitates calculation of Intraclass Correlation coefficients in order to determine the required sample size. The purpose of this study is to determine Intraclass Correlation coefficients for a number of outcome measures at the primary care practice level. The CEART study is a randomized trial testing the effectiveness of translating ATP III guidelines into clinical practice, with primary care physician practices as the unit of randomization and patients as the unit of data collection. The Intraclass Correlation coefficient (ICC) was<0.02 and the design effect ranged from 1.0 to 2.3, respectively, for weight, total cholesterol, LDL, non-HDL, glucose, creatinine, and % at non-HDL goal. For smoking status, body mass index, systolic blood pressure, HDL cholesterol triglycerides, total cholesterol/HDL ratio and % at LDL goal, the ICC was 0.02–0.047 and the design effect was 2.6–4.1. The largest ICCs (0.05–0.12) and design effects (4.4–9.4) were found for height and diastolic blood pressure. These findings suggest that cluster randomization may substantially increase the sample size necessary to maintain adequate statistical power for selected outcomes such as diastolic blood pressure studies compared with simple randomization for most outcomes evaluated in this study where the design effect is small to moderate. Overall, the ICCs presented will be useful in calculating sample sizes at the primary care level.
Burkhardt Seifert - One of the best experts on this subject based on the ideXlab platform.
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confidence intervals for Intraclass Correlation in inter rater reliability
Scandinavian Journal of Statistics, 2003Co-Authors: Valentin Rousson, Theo Gasser, Burkhardt SeifertAbstract:AbstractCalculation of a confidence interval for Intraclass Correlation to assess inter-rater reliability is problematic when the number of raters is small and the rater effect is not negligible. Intervals produced by existing methods are uninformative: the lower bound is often close to zero, even in cases where the reliability is good and the sample size is large. In this paper, we show that this problem is unavoidable without extra assumptions and we propose two new approaches. The first approach assumes that the raters are sufficiently trained and is related to a sensitivity analysis. The second approach is based on a model with fixed rater effect. Using either approach, we obtain conservative and informative confidence intervals even from samples with only two raters. We illustrate our point with data on the development of neuromotor functions in children and adolescents.
