Services
The Research Process at Applied Inference
I have an extensive background using quantitative and qualitative research methods, backed by a PhD in Physiological Psychology and Quantitative Methods and more than 25 years experience as an evaluator. I have done this work as an employee of the University of Washington, an employee of a local nonprofit, and as Applied Inference since 1987.
Overall, I design and implement research and evaluation projects. I gather both qualitative and quantitative data and apply qualitative and statistical methods to new or existing data to identify underlying patterns that may help improve services to clients or identify unmet need. Depending on when I get involved, a project may include creating the evaluation plan, or it may require implementing some component of an existing plan. Every project requires some subset of these steps:
- Proposal or Evaluation Plan
- Problem Analysis
- Research Design
- Data Collection and Management
- Analysis
- Reporting and Presentation
Site Content
Proposal or Evaluation Plan
I sometimes get involved with a project when it is just a proposal that needs an evaluation section. To create a credible evaluation plan, it is critical to learn the standards and expectations of the prospective funder, and to develop a thorough understanding of the project. When I am called in at this point, I carefully review the proposal and create a Logic Model of the proposed project to ensure that I understand it. The evaluation plan follows the logic model.
Problem Analysis
I meet with clients to gain an understanding of their research needs and, depending on the phase of the project, the data availability. We determine which questions existing data will support and what additional data will be required.
Research Design
Careful research design enables the client to draw stronger conclusions at the end of the research.
Data Collection and Management
Data collection includes extraction from paper or electronic files, interviews and focus groups, observation, and surveys. Database management includes variable definition, data coding and capture, detecting and reconciling erroneous data, creating new variables by combining initial variables, and combining separate datasets.
Analysis
The heart of a research project is the initial test of the research question: is it working? followed by data exploration to discover unanticipated relationships. I employ all appropriate statistical procedures from the most basic to very advanced, always mindful of their strengths as well as weaknesses and limitations.
Reporting and Presentation
Results must be presented in a form that is understandable to a lay audience and credible to a scientific audience. This usually involves producing a technical and detailed narrative report (with tables and graphs), which serves as the basis of reports for specific audiences (such as publication in scientific journals, informing the media, and influencing public policy makers).