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.
Data Sources
What is it? Data sources refer to where your data comes from. The most common data sources are primary and secondary data sources. Primary (quantitative) data sources are the information collected directly by researchers specifically either using observation or experiments. Secondary data are the existing data collected by a party for other purposes at different time in the past and not related to the research team. In the medical field, a common type of secondary data is retrospective chart review, also known as a medical record. Both primary and secondary data sources have their advantages and disadvantages.
As research advances, there are more types of data sources. For example, simulation data is increasingly applied to imitate the data of a real-world process using computer test models. It is widely used in various fields, such as predicting weather, modeling economy, and investigating chemical reactions. Other common data sources are systematic reviews and meta-analyses. Both types of reviews collect and summarize data and evidence to address a specific topics. The type of research data you need to obtain is determined by your research purpose, research design, and accessibility of the data. Selecting a data source may impact the way you manage the data later.
How can we help you?
- Design how to collect primary data and what measures should be included
- Review secondary data and extract useful information for recommendations
- Perform simulation based on specific request
- Provide suggestions on database search
- Provide strategies on study selection and data collection process in systematic review and meta-analysis
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Learn MoreArticles and White Papers About Data Sources
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Read MoreFAQ About Data Sources
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