Dataset Information

Statistical methods for evaluating the correlation between timeline follow-back data and daily process data with applications to research on alcohol and marijuana use.

ABSTRACT: BACKGROUND:Retrospective timeline follow-back (TLFB) data and prospective daily process data have been frequently collected in addiction research to characterize behavioral patterns. Although previous validity studies have demonstrated high correlations between these two types of data, the conventional method adopted in those studies was based on summary measures that may lose critical information and the Pearson's correlation coefficient that has an undesirable property. This study proposes the functional concordance correlation coefficient to address these issues. METHODS:We use real data collected from a randomized experiment to demonstrate the applications of the proposed method and compare its analytical results with those of the conventional method. We also conduct a simulation study based on the real data to evaluate the level of overestimation associated with the conventional method. RESULTS:The results of the real data example indicate that the correlation between these two types of data varies across substances (alcohol vs. marijuana) and assessment schedules (daily vs. weekly). Additionally, the correlations estimated by the conventional method tend to be higher than those estimated by the proposed method. The simulation results further show that the magnitude of overestimation associated with the conventional method is greatest when the true correlation is medium. CONCLUSIONS:The findings of the real data example imply that daily assessments are particularly beneficial for characterizing more variable behaviors like alcohol use, whereas weekly assessments may be sufficient for low variation events such as marijuana use. The proposed method is a better approach for evaluating the validity of TLFB data.

SUBMITTER: Liu W

PROVIDER: S-EPMC6544482 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Statistical methods for evaluating the correlation between timeline follow-back data and daily process data with applications to research on alcohol and marijuana use.

Liu Wanjun W Li Runze R Zimmerman Marc A MA Walton Maureen A MA Cunningham Rebecca M RM Buu Anne A

Addictive behaviors 20181221

<h4>Background</h4>Retrospective timeline follow-back (TLFB) data and prospective daily process data have been frequently collected in addiction research to characterize behavioral patterns. Although previous validity studies have demonstrated high correlations between these two types of data, the conventional method adopted in those studies was based on summary measures that may lose critical information and the Pearson's correlation coefficient that has an undesirable property. This study prop ...[more]

PMID: 30611576

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Project description:BackgroundAlthough there is increasing interest in reporting results of environmental research efforts back to participants, evidence-based tools have not yet been applied to developed materials to ensure their accessibility in terms of literacy, numeracy, and data visualization demand. Additionally, there is not yet guidance as to how to formally assess the created materials to assure a match with the intended audience.MethodsRelying on formative qualitative research with participants of an indoor air quality study in Dorchester, Massachusetts, we identified means of enhancing accessibility of indoor air quality data report-back materials for participants. Participants (n = 20) engaged in semi-structured interviews in which they described challenges they encountered with scientific and medical materials and outlined written and verbal communication techniques that would help facilitate engagement with and accessibility of environmental health report-back materials. We coupled these insights from participants with best practice guidelines for written materials by operationalizing health literacy tools to produce accessible audience-informed data report-back materials.ResultsThe resulting data report-back materials had a 7th -grade reading level, and between a 4th -8th grade level of overall document complexity. The numeracy skills required to engage with the material were of the lowest demand, and we incorporated best practices for risk communication and facilitating understanding and actionability of the materials. Use of a rigorous assessment tool provides evidence of accessibility and appropriateness of the material for the audience.ConclusionsWe outline a process for developing and evaluating environmental health data reports that are tailored to inspire risk-reduction actions, and are demonstrably accessible in terms of their literacy, numeracy, and data visualization demand. Adapting health literacy tools to create and evaluate environmental data report-back materials is a novel and evidence-based means of ensuring their accessibility.

Project description:BackgroundUsing observational data to assess the relative effectiveness of alternative cancer treatments is limited by patient selection into treatment, which often biases interpretation of outcomes. We evaluated methods for addressing confounding in treatment and survival of patients with early-stage prostate cancer in observational data and compared findings with those from a benchmark randomized clinical trial.MethodsWe selected 14 302 early-stage prostate cancer patients who were aged 66-74 years and had been treated with radical prostatectomy or conservative management from linked Surveillance, Epidemiology, and End Results-Medicare data from January 1, 1995, through December 31, 2003. Eligibility criteria were similar to those from a clinical trial used to benchmark our analyses. Survival was measured through December 31, 2007, by use of Cox proportional hazards models. We compared results from the benchmark trial with results from models with observational data by use of traditional multivariable survival analysis, propensity score adjustment, and instrumental variable analysis.ResultsProstate cancer patients receiving conservative management were more likely to be older, nonwhite, and single and to have more advanced disease than patients receiving radical prostatectomy. In a multivariable survival analysis, conservative management was associated with greater risk of prostate cancer-specific mortality (hazard ratio [HR] = 1.59, 95% confidence interval [CI] = 1.27 to 2.00) and all-cause mortality (HR = 1.47, 95% CI = 1.35 to 1.59) than radical prostatectomy. Propensity score adjustments resulted in similar patient characteristics across treatment groups, although survival results were similar to traditional multivariable survival analyses. Results for the same comparison from the instrumental variable approach, which theoretically equalizes both observed and unobserved patient characteristics across treatment groups, differed from the traditional multivariable and propensity score results but were consistent with findings from the subset of elderly patient with early-stage disease in the trial (ie, conservative management vs radical prostatectomy: for prostate cancer-specific mortality, HR = 0.73, 95% CI = 0.08 to 6.73; for all-cause mortality, HR = 1.09, 95% CI = 0.46 to 2.59).ConclusionInstrumental variable analysis may be a useful technique in comparative effectiveness studies of cancer treatments if an acceptable instrument can be identified.

Dataset Information

Statistical methods for evaluating the correlation between timeline follow-back data and daily process data with applications to research on alcohol and marijuana use.

Publications

Statistical methods for evaluating the correlation between timeline follow-back data and daily process data with applications to research on alcohol and marijuana use.

Similar Datasets

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