Quantitative Design
When you are planning on a study, you always want to ensure that the evidence obtained enables you to address the research problem effectively, logically, and as unambiguously as possible. If you begin the investigation too early, without thinking critically about what information is required, the overall problem may not be adequately addressed and the validity of the study will be undermined. Research design integrates all elements needed for the study to maximize validity and balance feasibility prior to beginning the data collection. Our quantitative design planning includes descriptive and experimental designs to provide you a blueprint for the collection, measurement, and analysis of data.
Quantitative Planning
What is it? Quantitative design planning is systematically and comprehensively designing your research in order to generate evidence to answer research questions. The end goal of research is to solve a problem and fill a gap – therefore, problem identification is the starting point. The identified research problem should always come from a thorough understanding of the literature. Research questions and hypotheses should properly align with the research problem.
Research design planning involves thinking through the most appropriate methodology to collect data. Cultural contexts need to be considered, which include background beliefs and practices that guide behaviors. You also want to ensure that the design is feasible, that participants can complete the project and results generalized to the larger population. Our consultants can help you identify the problem, refine the research question(s), and provide a systematic plan for your design.
How can we help you?
- Initial Literature Review and gap identification
- Provide guidance on seeking collaborations
- Refine research questions and hypothesis
- Align research problem, goals/purposes, research question, and hypothesis
- Evaluate the feasibility of a research plan
- Assess replication and generalization
- Balance design effort and resources (time/money)
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FAQ About Quantitative Planning
There are numerous statistical analytic softwares and platforms capable of modeling and simulation based on known and variable inputs. Experience modeling these simulations helps to properly contextualize and dial results in order to apply and garner feedback useful to processes.
Secondary data sources publish research collected from academic, governmental, philanthropic, journalistic, medical and other sources to public, private, and academic channels. These secondary data sources can complement, replace, reshape, or enhance your research goals and approach.
Existing reviews and studies give access to best practices, market research information and infrastructure developments with limited cost in resources and time. It is incredibly valuable to understand which reviews/studies will be profitable and applicable to portions of your operations.
Combining offline and online data collection is normally straightforward provided that the collection mechanisms are compatible. Data is often collected in a CSV or other standard formatting procedure that can be exported to Excel or another software packaging system that can be cleaned and analyzed.
Everyone knowingly or unknowingly misses out on major data opportunities. Determining the usefulness and costs of acquiring or ignoring data opportunities generally requires a multidisciplinerian team of individuals with diverse research background and connection to data systems and sources.
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Peggy Ostrander, DNPc, APRN, FNP-C Plano, Texas