What’s it like to collaborate with us?
MAP Academy partners with scholars during all stages of their work to ensure success — from proposal development to data archiving and preservation after a project ends. Collaboration with our team may include all five phases of the research data life cycle, a framework developed by the UNL Research Data Strategy Task Force.
Research Supports
MAP Academy collaborates on research projects, providing support via an hourly rate rather than billing full-time equivalents (FTE) to a project. Rates are determined annually by UNL. Initial consultations to discuss project needs, goals and scope are complimentary, as well as proposal development activities. Available collaboration activities are outlined below. Please contact us to discuss specific project needs, including any supports that may not be listed below.
View Current Rates Get StartedProposal Development Supports
Let’s start the conversation! Our team is available to collaborate in developing funding proposals. We provide the following proposal development supports:
Planning
- Developing and collaborating on study/research designs.
- Crafting sampling and randomization plans.
- Conducting power analyses to inform sample size requirements and identify minimally detectable effect sizes.
- Informing data collection and data management procedures.
- Developing data management/sharing plans per funder requirements.
- Designing data analysis plans.
- Guiding plans for assessing intervention fidelity.
- Developing budgets for post-award supports and collaboration.
Research Implementation Supports
Our range of expertise allows us to contribute to funded research projects in a variety of ways, depending on your needs. We provide the following research implementation supports:
Data Infrastructure & Management
Database Development
- Creating Qualtrics surveys for online data collection.
- Building customized data systems for individual projects, including survey and data entry portals and custom data reports for analytic use.
- Integrating various software (e.g., Qualtrics) into customized project websites.
- Ensuring methods for secure data transfer from field-based research sites.
Data Management
- Data cleaning (e.g., flagging errant data patterns, naming variables, merging datasets) and creating composite variables (e.g., scoring measures).
- Providing best practices training in data/statistical software (e.g., SPSS, SAS, Mplus, R) for GRAs and project staff.
Data Curation Consultation
- Supporting data curation, the ongoing processing and maintenance of data throughout its life cycle to ensure long-term accessibility, sharing and preservation.
Applied Analytics
Analysis
- Performing descriptive and inferential analyses.
- Analytic methods may include but are not limited to general/generalized linear modeling, mixed modeling (e.g., multilevel or hierarchical linear modeling, growth modeling), dyadic data modeling, latent variable modeling (e.g., structural equation modeling, item response theory, factor analysis, latent class analysis), and mediation and moderation analysis.
- Using complex survey analysis methods to analyze data from large-scale national and international survey studies (e.g., ECLS, NAEP, PISA).
- Conducting qualitative data analysis.
- Guiding integration procedures for mixed methods studies.
Measurement
- Developing appropriate data collection protocols based on the measurement study design.
- Supporting best practices for measure development in areas such as item writing, general design and administration.
- Conducting psychometric analyses (e.g., factor analysis, reliability analysis) for a measure.
- Evaluating existing psychometric data to appraise the degree of reliability and validity evidence for existing measure(s).
Sharing
- Creating appropriate visual data displays.
- Collaborating on the preparation of manuscripts, reports and other dissemination materials.
