Dataset Information

Statistical Methods for Cardiovascular Researchers.

ABSTRACT:

Rationale

Biostatistics continues to play an essential role in contemporary cardiovascular investigations, but successful implementation of biostatistical methods can be complex.

Objective

To present the rationale behind statistical applications and to review useful tools for cardiology research.

Methods and results

Prospective declaration of the research question, clear methodology, and study execution that adheres to the protocol together and serve as the critical foundation of a research endeavor. Both parametric and distribution-free measures of central tendency and dispersion are presented. T testing, ANOVA, and regression analyses are reviewed. Survival analysis, logistic regression, and interim monitoring are also discussed. Finally, common weaknesses in statistical analyses are considered.

Conclusions

Biostatistics can be productively applied to cardiovascular research if investigators (1) develop and rely on a well-written protocol and analysis plan, (2) consult with a biostatistician when necessary, and (3) write results clearly, differentiating confirmatory from exploratory findings.

SUBMITTER: Moye L

PROVIDER: S-EPMC4745995 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Publications

Statistical Methods for Cardiovascular Researchers.

Moyé Lem L

Circulation research 20160201 3

<h4>Rationale</h4>Biostatistics continues to play an essential role in contemporary cardiovascular investigations, but successful implementation of biostatistical methods can be complex.<h4>Objective</h4>To present the rationale behind statistical applications and to review useful tools for cardiology research.<h4>Methods and results</h4>Prospective declaration of the research question, clear methodology, and study execution that adheres to the protocol together and serve as the critical foundat ...[more]

PMID: 26846639

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Project description:Background:There is increasing evidence that research misbehaviour is common, especially the minor forms. Previous studies on research misbehaviour primarily focused on biomedical and social sciences, and evidence from natural sciences and humanities is scarce. We investigated what academic researchers in Amsterdam perceived to be detrimental research misbehaviours in their respective disciplinary fields. Methods:We used an explanatory sequential mixed methods design. First, survey participants from four disciplinary fields rated perceived frequency and impact of research misbehaviours from a list of 60. We then combined these into a top five ranking of most detrimental research misbehaviours at the aggregate level, stratified by disciplinary field. Second, in focus group interviews, participants from each academic rank and disciplinary field were asked to reflect on the most relevant research misbehaviours for their disciplinary field. We used participative ranking methodology inducing participants to obtain consensus on which research misbehaviours are most detrimental. Results:In total, 1080 researchers completed the survey (response rate: 15%) and 61 participated in the focus groups (3 three to 8 eight researchers per group). Insufficient supervision consistently ranked highest in the survey regardless of disciplinary field and the focus groups confirmed this. Important themes in the focus groups were insufficient supervision, sloppy science, and sloppy peer review. Biomedical researchers and social science researchers were primarily concerned with sloppy science and insufficient supervision. Natural sciences and humanities researchers discussed sloppy reviewing and theft of ideas by reviewers, a form of plagiarism. Focus group participants further provided examples of particular research misbehaviours they were confronted with and how these impacted their work as a researcher. Conclusion:We found insufficient supervision and various forms of sloppy science to score highly on aggregate detrimental impact throughout all disciplinary fields. Researchers from the natural sciences and humanities also perceived nepotism to be of major impact on the aggregate level. The natural sciences regarded fabrication of data of major impact as well. The focus group interviews helped to understand how researchers interpreted 'insufficient supervision'. Besides, the focus group participants added insight into sloppy science in practice. Researchers from the natural sciences and humanities added new research misbehaviours concerning their disciplinary fields to the list, such as the stealing of ideas before publication. This improves our understanding of research misbehaviour beyond the social and biomedical fields.

Dataset Information

Statistical Methods for Cardiovascular Researchers.

Rationale

Objective

Methods and results

Conclusions

Publications

Statistical Methods for Cardiovascular Researchers.

Similar Datasets

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