This course is the first is a two-part scale development course series that introduces students to the systematic process of developing multi-item scale measures and survey instruments. Examples include measures of various social and psychological variables that might be assessed in health, medicine, journalism, or other related research areas. After a brief theoretical introduction to topics such as defining a construct and types of validity, we will turn to applied issues such as what is the optimal scale development process and how (and when) can you deviate from that process. We will also address practical issues around questionnaire design such as how to construct a “good” survey instrument that has a natural flow, minimizes participant burden, has appropriate response options and other common concerns in scale development and design. We will focus on real-life examples to demonstrate the scale development process. Although we will briefly discuss the kinds of quantitative techniques that are commonly used in the scale development process, this course will not cover the application of these methods. Quantitative methods for scale development will be covered in Part 2 of this course series.

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This online training session will provide an introduction to qualitative research methods. Participants will have the opportunity to ask questions and share experiences conducting qualitative research. Topics include: differences between quantitative and qualitative research, qualitative research methodologies, strategies for qualitative data collection, and methods of qualitative data analysis.

This event may be recorded. Materials such as slides or handouts will be shared with documented attendees only.

Presenters:
MaryBeth Grewe, MPH
Program Manager, Qualitative Research Service
Research Specialist, Patient and Community Engagement in Research (PaCER) Program

Simone Frank, MPH
Senior Project Manager, Patient and Community Engagement in Research (PaCER) Program
Research Specialist, Qualitative Research Service

For questions about this training, please contact MaryBeth Grewe at This email address is being protected from spambots. You need JavaScript enabled to view it..

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Join us for a laptop-optional workshop to learn about using exploratory data analysis (EDA) as part of a data analysis plan for clinical research. Code samples will be provided in both R and Python.

In this workshop, you will learn how to:

• Rearticulate research question with respect to collected data
• Design and implement a data analysis plan
• Use appropriate exploratory data analysis (EDA) for variable and question types

Prerequisites: No prerequisite knowledge needed. Some exposure to data analysis in R and/or Python may be beneficial.

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This workshop is co-sponsored by the Data Science and AI Academy at NC State University and the Informatics and Data Science program at NC TraCS Institute.