Enhancing the validity and utility of randomized clinical trials in addictions treatment research: III. Data processing and statistical analysis.
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 processi...
| Publicado en: | Addiction Vol. 102; no. 9; pp. 1356 - 1365 |
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| Autores principales: | , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
Sep2007
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=106011285&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106011285 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: Sep2007 vid: 102 iid: 9 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 106011285 106011285 2009664404 10.1111/j.1360-0443.2007.01864.x NLM17511751 106011285 ppf: 1356 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Enhancing the validity and utility of randomized clinical trials in addictions treatment research: III. Data processing and statistical analysis. aug: au: Del Boca FK Darkes J sug: subj: Behavior, Addictive Epidemiology Clinical Trials Substance Use Disorders Epidemiology Data Analysis, Statistical Models, Statistical Reproducibility of Results Study Design Human ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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