Methodological and Study Design
This is a foundational service where consultants assist researchers before data collection begins to ensure the study is structured to validly answer research questions and to frame their scientific questions as testable statistical hypotheses.
- Protocol DevelopmentParticipating in the creation of research protocols with specific considerations for design and methods.
- Study Hypothesis FormulationHelping researchers frame scientific questions as testable statistical hypotheses.
- Study/Experimental StructureGuidance on experimental design, including randomized blocks, factorial designs, and clinical trial protocols.
- Sample Size and Power DeterminationCalculating the necessary sample size and performing power analysis to ensure the study can detect significant effects.
- Survey DevelopmentAssistance with questionnaire design, sampling methods, and testing for reliability and validity.
Grant Proposal Support
Many units provide specialized assistance during the pre-award phase to increase the competitiveness of grant applications.
- Methodological JustificationSCC participates directly in drafting or editing the "design and methods" sections of grant applications.
- Statistical JustificationSCC specifically assist with sample size determination to ensure the study is appropriately scaled to meet its objectives.
- Data Management Plans (DMP)Providing guidance on data curation and compliance with federal funding requirements.
- FeasibilityConsultants help determine if the proposed research goals are achievable with the available resources and population size.
Data Management and Preparation
Centers offer practical support for handling research data to ensure it is organized correctly for analysis.
- Organization and FormattingAdvice on data input, creating dataset structures, and choosing appropriate file formats.
- Preparation and CleaningSuggestions for data manipulation and cleaning to prepare raw files for statistical processing.
- Security and PrivacyGuidance on handling de-identified human subjects' data and maintaining IRB compliance.
Data Analysis and Statistical Modeling
This core service involves the application of traditional and modern statistical techniques to answer research questions.
- Exploratory AnalysisSummarizing data through descriptive statistics and initial visualization.
- ModelingRecommending and implementing methods such as regression, time series analysis, causal inference, and machine learning (classification and prediction).
- Advanced MethodologiesSupport for complex challenges like "Big Data" analytics, Bayesian inference, and model validation.
Interpretation and Dissemination
Consultants help researchers translate complex statistical output into meaningful conclusions for publication.
- Results InterpretationExplaining analysis outputs to address the original scientific goals.
- Visual RepresentationCreating publication-quality graphs, charts, and specialized data visualizations.
- Manuscript SupportAssisting with the writing of results sections and responding to peer-reviewer comments.
Strategic Timing and Collaboration
The sources emphasize that the effectiveness of this help is often tied to how early the center is involved:
- Early EngagementResearchers are strongly encouraged to seek consultation during the initial stages of defining endpoints and writing protocols.
- Long-Term PartnershipSome centers, like Penn State, offer "Long-Term Collaboration" for projects that require extensive work over an extended period, which can be essential for complex, multi-year grant-funded research.
- Interdisciplinary SupportCenters often bridge the gap between statistics and other fields, such as the life sciences, to ensure the statistical methodology is appropriate for the specific discipline.