Você se depara com resultados de análise de dados conflitantes. Como você pode garantir que suas conclusões permaneçam imparciais?

A researcher's biggest enemy is having a pre-decided result in mind and expecting the data analysis results to match it. Confusion, panic sets in when they do not match. When I did a research on the correlation of language learning skills and the mode of learning, I 'expected' a positive correlation while the data analysis showed there weren't any. That was a big mental roadblock to overcome. In such cases, it is best to cross-check the methods and data, talk to your guides and peers and most importantly, lay everything bare (which is what I did). Never think of manipulating the data or the methodology to get your 'desired' result. Data fudging or manipulation in academia is a crime that no one associated with academia will tolerate!!

The fundamental point is keeping in mind two key principals in clinical research, equipoise and uncertainty principle. By following these principles you focus on the research question and avoid biases towards the answer.

When I encounter conflicting data, I take several steps to ensure impartiality: Reassess the Data: I double-check the data sources and methodologies used to identify potential errors or inconsistencies. Seek Multiple Perspectives: Consulting with peers or experts offers fresh insights that help uncover biases or alternative interpretations. Use Diverse Analytical Methods: Applying different analytical techniques can help validate results and clarify discrepancies. Stay Transparent: I document every decision and rationale to maintain clarity and avoid subjective conclusions. This approach helps me stay objective and reach balanced conclusions.

To ensure your conclusions remain unbiased amid conflicting data analysis results, critically evaluate the quality and methodology of each data source. Seek corroboration from multiple sources, apply consistent analytical techniques, and consider alternative explanations. Document your process transparently and be open to revising your conclusions based on new evidence or insights.

When I encounter conflicting data ,I take those steps (5R): Recognize the source and nature of the data. Refine the purpose and scope of the analysis. Request additional or alternative data. Rate and compare the data. Relay and justify the analysis.