Dataset Information

Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.

ABSTRACT: Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454) is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. The new approach allows for a more comprehensive and effective use of MI data when testing mediation models.

SUBMITTER: Papa LA

PROVIDER: S-EPMC4643137 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.

Papa Lesther A LA Litson Kaylee K Lockhart Ginger G Chassin Laurie L Geiser Christian C

Frontiers in psychology 20151113

Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various ...[more]

PMID: 26617536

Similar Datasets

Project description:PurposeTo develop a statistical approach that compares patient selection strategies across clinical trials and apply this approach to acute ischemic stroke clinical trials to identify the optimal inclusion criteria.MethodsWe developed a statistical approach that compares the number needed to treat to achieve one success (NNT) along with the number needed to screen to achieve one success (NNS) and assesses if there are significant differences in inclusion criteria, treatment course, and clinical outcome among patients that may have been included/excluded in the trials. We applied this approach to the study population from four recent positive acute stroke clinical trials: MR CLEAN, EXTEND-IA, ESCAPE, and SWIFT PRIME, applying published trial criteria to an independent registry of 612 acute stroke patients, since we did not have access to the complete trial data.ResultsAlthough reported NNT were similar for EXTEND-IA, SWIFT PRIME and ESCAPE, and somewhat higher for MR CLEAN, NNS varied across the trials from 21 for EXTEND-IA, 27 for MR CLEAN, to 46 for ESCAPE and 64 for SWIFT PRIME, reflecting less and more stringent inclusion criteria, respectively. Although there were significant differences in imaging biomarkers and other clinical characteristics among patients that may have been included/excluded in the trials, these differences did not translate to significant differences in treatment course or clinical outcomes.ConclusionsOur study proposes a robust statistical approach that can be applied to a larger pooled trial dataset, if made available, to objectively compare across clinical trials and inform inclusion criteria of future trials. Pooled analysis of the acute stroke trial data is needed to determine which imaging biomarker inclusion criteria are critical and which may be relaxed. If this procedure were applied across the pooled trial data, it could decrease costs and refine the design of future trials to be the most efficacious for the greatest number of patients.

Dataset Information

Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.

Publications

Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets