> For the complete documentation index, see [llms.txt](https://whri.gitbook.io/whristatresources.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whri.gitbook.io/whristatresources.com/research/research-guidance-and-relevant-documentation.md). # Research Guidance and Relevant documentation Everything you need to know about research {% tabs %} {% tab title="Research" icon="pen-line" %} Guidance, tools, and resources supporting the research process from question development to publication. * **Developing a Research Question**\ Explains how to move from a broad topic to a focused, feasible, and researchable question. It covers the characteristics of a strong research question, literature reviews and gap identification, use of the PICO framework, examples for different study designs, and considerations for data availability, privacy, FAIR principles, equity, and feasibility.\ [Developing a Research Question](/whristatresources.com/research/developing-a-research-question.md) * **Why Write a Study Protocol?**\ Explains how a study protocol serves as the blueprint for a research project by documenting what will be studied, why it is important, and how the research will be conducted. The guidance covers study objectives, design, population, interventions, outcomes, data collection and management, statistical analysis, ethics, timelines, team responsibilities, dissemination, and strategies for maintaining research quality, transparency, and reproducibility.\ [Why Write a Study Protocol?](/whristatresources.com/why-write-a-study-protocol.md) * **Guidance for Hypothesis Testing Framework**\ Explains the full hypothesis-testing process, from reviewing the research question, study protocol, design, variables, and data quality to defining null and alternative hypotheses and choosing methods appropriate to the outcome, data structure, and study objectives. It also covers statistical assumptions, significance levels, p-values, confidence intervals, effect sizes, clinical relevance, modelling approaches, and the documentation and secure archiving of data, code, analytical decisions, and results.\ [Guidance for Hypothesis Testing Framework](/whristatresources.com/guidance-for-hypothesis-testing-framework.md) * **Publishing with Purpose**\ Covers journal selection, manuscript planning, title and abstract development, and the effective presentation of the introduction, methods, results, and discussion, with emphasis on transparency, reporting standards, authorship, and responsible publication practices.\ [Publishing with Purpose: Guidance for Research Paper Writing](/whristatresources.com/publishing-with-purpose-guidance-for-research-paper-writing.md) * **Relevant video describing the above documents**\ ***This video*** presents a practical framework for moving from a clearly defined research question through study design, data collection, statistical analysis, interpretation, and publication. It emphasizes how decisions made at each stage of the research process influence the quality, validity, and usefulness of the final results.\ ***WHRI Analytical Framework: Bridging the Gap from Research Question to Publication***
{% endtab %} {% tab title="Data" icon="pen-line" %} Guidance, tools, and resources supporting data management processes and procedures * **Principles of data governance and management**\ This document explains how data governance and Data Management Plans support high-quality, secure, ethical, and reproducible research. It outlines the main stages of the data lifecycle and describes how research teams should define variables, data sources, collection methods, timing, staff responsibilities, standardization procedures, data-entry tools, access controls, and quality assurance processes. It also distinguishes data governance, which establishes policies and oversight, from data management, which puts those requirements into practice throughout the project. \ [Data principles and governance](/whristatresources.com/data-principles-and-governance.md) * **Designing a Research Database**\ This document provides practical guidance for managing research data across the data lifecycle, with a focus on governance, planning, collection, quality assurance, documentation, and security. It explains how a Data Management Plan translates ethical, legal, and institutional requirements into clear procedures for identifying variables, selecting data sources and collection methods, defining timelines, assigning staff responsibilities, standardizing instruments, and documenting data-entry systems. The guidance also distinguishes data governance, which establishes policies and oversight, from data management, which implements those requirements in practice, supporting accurate, secure, transparent, and reproducible research.\ [Designing a Research Database: Structure, Documentation, and Governance](/whristatresources.com/designing-a-research-database-structure-documentation-and-governance.md) * **Data cleaning processes and procedures**\ This document provides a standardized, step-by-step framework for preparing research data for analysis, moving from raw data extraction to cleaned, transformed, and final analytical datasets while emphasizing consistency, transparency, reproducibility, privacy, and compliance with regulations such as FIPPA and PIPEDA. It highlights key practices including validating dataset structure, checking missing values, outliers and duplicates, standardizing formats and units, documenting recoding and transformations, maintaining updated data dictionaries, securely linking datasets using randomized IDs, and carefully verifying merges and final datasets before analysis or sharing\ [Data cleaning processes and procedures](/whristatresources.com/data-cleaning-processes-and-procedures.md) * **Relevant video describing the above documents**\ ***This video*** explains what makes a dataset ready for statistical analysis, including how data should be structured, cleaned, coded, and documented before analysis begins. It highlights common data-quality problems and the steps needed to transform raw data into a reliable, analysis-ready dataset.\ ***From Mess to Meaning: What Makes a Dataset Analysis Ready***\
{% endtab %} {% tab title="Clinical trials" icon="pen-line" %} Series of documents related to clinical tirals * This document provides a practical summary of the updated **ICH E6(R3) Good Clinical Practice (GCP) guideline** and highlights key differences from ICH E6(R2). It focuses on the shift toward **quality by design, critical thinking, proportionality, and risk-based approaches**, with greater emphasis on identifying what is most important for participant safety and the reliability of trial results. The document also summarizes changes related to data governance, electronic systems, oversight, documentation, and the integration of protocol development, data collection, monitoring, statistical analysis, and reporting across the clinical trial lifecycle.\ [Summary of ICH E6(R3) Good Clinical Practice and Comparison with ICH E6(R2)](/whristatresources.com/summary-of-ich-e6-r3-good-clinical-practice-and-comparison-with-ich-e6-r2.md) {% endtab %} {% endtabs %} **Authorship and Intellectual Property**\ This guidance was developed by Sabina Dobrer as part of the WHRI Analytical Framework. Please provide appropriate attribution when referencing, reproducing, or adapting this material. AI tools were applied to improve clarity and grammar. The content, structure, and analytical framework were developed independently by the author. *** --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://whri.gitbook.io/whristatresources.com/research/research-guidance-and-relevant-documentation.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.