SSRI offers one-on-one advice to support Duke students and faculty in planning and conducting their research and works to help faculty connect with collaborators and identify opportunities to secure funding to advance their research.
Research originates with a great question or idea, yet requires much more–such as testable hypotheses, useful data, coded interviews, statistical or spatial software, and the ability to interpret and disseminate findings.
Getting from great idea to feasible project can require dodging pitfalls, particularly for the novice researcher or for collaborative teams that apply a new method or tool.
SSRI is here to help! Our Connection Bar offers a consulting service staffed by advanced graduate students, postdoctoral fellows, and SSRI research staff. This team is available by appointment to consult on all stages of the research process. Team members can offer quick advice on such topics as
- Model development and hypothesis specification
- Duke data resources
- Crafting and conducting surveys and interviews
- Qualtrics survey software
- Common statistical procedures, such as frequencies, crosstabs, OLS and logistic regression
- Common statistical software, including R, SPSS, Stata and SAS
- Content analysis, ethnography and coding of textual information
- NVivo qualitative software
Duke faculty and students: Schedule a consultation
Community Organization Evaluation Consulting
SSRI and Duke Civic Engagement are partnering to offer an opportunity for community-based organizations to build skills and get feedback in evaluation, applied research and empirical/data needs (e.g., survey design / implementation, interview and focus group design / implementation, and foundations of data management) via individualized consultation sessions.
Need help? Reach out via email and a member of our team will chat about any questions or concerns.
SSRI research staff can offer a core set of materials online to support Duke faculty working to serve their students during this unusual time. Below is a short list of the kinds of materials we are prepared to offer. These materials can be presented synchronously or asynchronously; with adequate advance notice, the materials to the needs of a particular class.
To support the University’s efforts during this time, we will make these materials available as requested at to faculty, departments, or schools insofar as we are able to do so. Requests will generally be honored on a first-come, first-serve basis.
Designed for researchers who are planning to collect original data and considering how to select one or more methods for doing so. The workshop begins with a review of effective and clear research question formulation and proceeds to a discussion of the advantages and opportunities, (as well as limitations of various data collection methods and associated analytic techniques), including survey research, in-depth interviewing, ethnography, focus groups, and text analysis. In addition, the workshop will attend to logistical and theoretical considerations in implementing each of these research approaches.
Provides an overview of key steps in the qualitative research process. Topics covered include creating an interview guide, conducting interviews, coding, analyzing data, and reporting results.
Prepares researchers to transform interview transcripts into analyzable data, and introduces foundational skills in qualitative data analysis. Participants will be introduced to the most common coding strategies deployed in social science to analyze data collected through in-depth interviews, focus groups, participant observation, and/or archival analyses of text.
Provides an introduction to a range of qualitative research methods as well as an overview of the strengths and weaknesses of each approach. Qualitative research methods, including in-depth interviews, focus groups, archival analysis, and participant observation, vary considerably in the resources and time required to execute them reliably, and in the types of data they generate. Which data collection techniques are appropriate to which kinds of research questions and projects, and how do you execute these methods well? How are issues of reliability and validity considered and weighed in qualitative research? We will also explore different ways of managing your data prior to commencing data collection in order to facilitate the transition to data analysis. Some time will be given to the role of NVivo software in facilitating data management and preparing for data analysis.
Introduces researchers to NVivo, a qualitative data analysis software available for free download through Duke OIT. Participants will learn strategies for analyzing text-based data in NVivo, such as transcribed interviews and focus groups, documents, and literature. Topics will include how to import data, create nodes and code, tips for formatting transcriptions, and basic queries and visualizations. This workshop will cover NVivo in both the PC and the Mac environment.
Examines question wording and questionnaire design for online and paper questionnaires. This presentation does not include programming (which is offered in the separate Qualtrics presentation), but focuses on the conceptual issues and considerations underpinning questionnaire design, question wording, and response options. It also provides an introduction to conducting survey experiments, including a brief motivation for when and why to use an experiment, common experimental designs, constructing experimental manipulations, and analysis.
Examines questionnaire design for online and paper questionnaires, such as screen layout and appearance, the use of images, and other aspects of the user interface which affect the accuracy of survey results. This presentation does not include programming, but focuses on the conceptual issues and considerations underpinning questionnaire design for online and paper designs. It also considers how such modes can be combined with other data collection modes, i.e., in-person or telephone.
Offers an introduction to Qualtrics survey software, a package available (at no cost to researchers) for use across Duke’s campus and medical center. This powerful, easy-to-use system is a great way to collect information online, whether as part of a research protocol or for administrative purposes, such as program evaluation. This workshop will introduce participants to the Qualtrics system, demonstrate how to set up an account, create a questionnaire and access its results. It will also cover some basic tools that can be used to customize the questionnaire to fit your needs, such as using display and skip logic to collect more detailed information from a subset of your audience.
Provides an introduction to community-engaged research and evaluation, as two (distinct, but related) forms of applied forms of research design. Topics covered include identifying distinct forms and types of community engaged research and evaluation, core steps in project design and execution, and common challenges.
Provides an overview of ways Excel can be used to structure, and even analyze data, and to create presentations. It starts with examining basic tools and functions in Excel (including ways that Excel can be used to manage textual data, to combine or divide data cells and sources, and to perform calculations such as sum, average, minimum, and maximum). It then proceeds to an overview of how to sort and transpose data and create graphs and tables. Finally, it reviews how to perform basic statistical operations, including counts and frequencies.
Offers an overview of the SAS programming language, focusing on data management activities. It includes a general overview of major SAS components (Program Editor, Log and Output) and the core concepts of SAS programming (DATA and PROC steps). It focuses on the process of importing and modifying data, including issues of importing/exporting data from other file formats, merging and concatenating data sets, and adding to or subsettting from datasets. Key SAS statements described include: PROC IMPORT, SET, MERGE, IF-THEN, and WHERE. It also includes considerations relevant to data analysis, including variable creation/recoding and descriptive analyses typically used in data management.