Frances K Del Boca1, Jack Darkes. 1. Department of Psychology, University of South Florida, Tampa, FL 33620-8200, USA. fdelboca@cas.usf.edu
Abstract
PURPOSE: This is the third paper in a series that reviews strategies for optimizing the validity and utility of randomized clinical trials (RCTs) in addictions treatment research. Whereas the two previous papers focused on design and implementation, here we address issues pertaining to data processing and statistical analysis. SCOPE: Recommendations for enhancing data quality and utility are offered in sections on data coding and entry; and data format, structure and management. We discuss the need for preliminary data analyses that examine statistical power; patterns of attrition; between-group equivalence; and treatment integrity and discriminability. We discuss tests of treatment efficacy, as well as ancillary analyses aimed at explicating treatment processes. CONCLUSIONS: Safeguards are necessary to protect data quality, and advance planning is needed to ensure that data formats are compatible with statistical objectives. In addition to treatment efficacy, statistical analyses should evaluate study internal and external validity, and investigate the change mechanisms that underlie treatment effects.
PURPOSE: This is the third paper in a series that reviews strategies for optimizing the validity and utility of randomized clinical trials (RCTs) in addictions treatment research. Whereas the two previous papers focused on design and implementation, here we address issues pertaining to data processing and statistical analysis. SCOPE: Recommendations for enhancing data quality and utility are offered in sections on data coding and entry; and data format, structure and management. We discuss the need for preliminary data analyses that examine statistical power; patterns of attrition; between-group equivalence; and treatment integrity and discriminability. We discuss tests of treatment efficacy, as well as ancillary analyses aimed at explicating treatment processes. CONCLUSIONS: Safeguards are necessary to protect data quality, and advance planning is needed to ensure that data formats are compatible with statistical objectives. In addition to treatment efficacy, statistical analyses should evaluate study internal and external validity, and investigate the change mechanisms that underlie treatment effects.
Authors: Veerle Raes; Cor A J De Jong; Dirk De Bacquer; Eric Broekaert; Jan De Maeseneer Journal: BMC Health Serv Res Date: 2011-05-25 Impact factor: 2.655