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.
Analysis Plan
What is it? The analysis plan is the ultimate demonstration of a well-formulated proposal and the starting point for running the analysis – essentially being a roadmap for how you will organize and analyze your data. It ensures that the analysis undertaken is conducted in a targeted manner. An analysis plan is composed of two elements. The first describes and summarizes the data in descriptive statistics – often using figures, tables, and statistics. The other identifies relevant statistical analysis procedures. As you develop an analysis plan for your research, you could ask yourself three questions:
- What is my research question?
- What is my research design?
- What is the level of measurement?
In addition to the analytic strategies you plan to use, don’t forget to include data preparation steps, such as strategies of examining data errors, checking missing data, and assumption tests. Developing an analysis plan is something we do very well; let us help you.
How can we help you?
- Develop and write data preparation procedures
- Develop and write data analysis plan
- Select alternative analysis plan
- Organize analysis plan with research questions and designs
- Refine analysis plan based on validated data
- Select appropriate software
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Learn MoreArticles and White Papers About Analysis Planning
Which Six Assumptions Of Multiple Regression Should You Always Test?
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Read MoreFAQ About Analysis Planning
There is a nearly endless supply of data opportunities. Awareness of potentially untapped resources often requires a research background beyond the specific field in question.
There are multiple platforms for collecting, organizing and analyzing data across different types of operations and infrastructures. The best fit for a particular use involves balancing cost, simplicity, data platform collection approaches, and technical capacity to use particular analytic methods.
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.
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Peggy Ostrander, DNPc, APRN, FNP-C Plano, Texas