Data Types
Quantitative Data
- Quantitative data is measurable, often used for comparisons, and involves counting of people, behaviors, conditions, or other discrete events (Wang, 2013).
- Quantitative data uses numbers to determine the what, who, when, and where of health-related events (Wang, 2013).
- Examples of quantitative data include: age, weight, temperature, or the number of people suffering from diabetes.
Qualitative Data
- Qualitative data is a broad category of data that can include almost any non-numerical data.
- Qualitative data uses words to describe a particular health-related event (Romano).
- This data can be observed, but not measured.
- Involves observing people in selected places and listening to discover how they feel and why they might feel that way (Wang, 2013).
- Examples of qualitative data include: male/female, smoker/non-smoker, or questionnaire response (agree, disagree, neutral).
- Example of qualitative data from a health care setting includes (Curry, Nembhard, & Bradley, 2009):
- Measuring organizational change.
- Measures of clinical leadership in implementing evidence-based guidelines.
- Patient perceptions of quality of care.
Data Sources
Primary Data Sources
- Primary data analysis in which the same individual or team of researchers designs, collects, and analyzes the data, for the purpose of answering a research question (Koziol & Arthur, nd).
- Advantages to Using Primary Data
- You collect exactly the data elements that you need to answer your research question (Romano).
- You can test an intervention, such as an experimental drug or an educational program, in the purest way (a double-blind randomized controlled trial (Romano).
- You control the data collection process, so you can ensure data quality, minimize the number of missing values, and assess the reliability of your instruments (Romano).
Secondary Data Sources
- Existing data collected for another purposes, that you use to answer your research question (Romano).
- Advantages of Working with Secondary Data
- Large samples
- Can provide population estimates : for example state data can be combined across states to get national estimates (Shaheen, Pan, & Mukherjee).
- Less expensive to collect than primary data (Romano)
- It takes less time to collect secondary data (Romano).
- You may not need to worry about informed consent, human subjects restriction (Romano).
- Issues in Using Secondary Data
- Study design and data collection already completed (Koziol & Arthur, nd).
- Data may not facilitate particular research question o Information regarding study design and data collection procedures may be scarce.
- Data may potentially lack depth (the greater the breadth the harder it is to measure any one construct in depth) (Koziol & Arthur, nd).
- Certain fields or departments (e.g., experimental programs) may place less value on secondary data analysis (Koziol & Arthur, nd).
- Often requires special techniques to analyze statistically the data.
References:
Curry, L. A., Nembhard, I. M., & Bradley, E. H. (2009). Qualitative and Mixed Methods Provide Unique Contributions to Outcomes Research. doi: 10.1161/CIRCULATIONAHA.107.742775
Koziol, N., & Arthur, A. (nd). An Introduction to Secondary Data Analysis CYFS Statistics and Measurement. Romano, P. S. Using secondary data. Department of Medicine and Pediatrics. University of California,.
Shaheen, M., Pan, D., & Mukherjee, S. Secondary data sources for research epidemiological and statistical considerations. Epidemiology and Biostatistics. Charles Drew University of Medicine and Science,
Wang, H. (2013). Data Detective: Finding the Gems of Health Data. Information and Education Services. University of Connecticut Health Center.
Source:https://www.nihlibrary.nih.gov/resources/subject-guides/health-data-resources