Who is eligible?
Students, faculty, and staff in the UNL Department of Psychology.
What consultation services are available?
You can schedule a consultation appointment at various stages of the research process. If you are planning a project, set up a meeting to discuss potential approaches to data analysis that can inform project design. If you have encountered challenges while analyzing data (e.g., model specification errors or fit issues, uncertainty about interpretation of results), meet with a member of the team to troubleshoot.
Students can also schedule a meeting to plan their quantitative training, including courses offered by the psychology department, other departments at UNL, and regional and national workshops and conference.
How do I schedule?
Please click on one of the links below to schedule a consultation appointment. Appointments are available via Zoom for 30 minutes.
Who should I schedule my appointment with?
Dr. Becca Brock has time reserved to offer consultation throughout the calendar year. During the academic year, an advanced graduate student (Harper Jones) is available for consultation.
Appointment Availability
Becca Brock, Ph.D.: Friday afternoons during fall semester. Click here to schedule with Becca.
Harper Jones, M.A.: Monday and Tuesday morning/early afternoon, Friday mornings. Click here to schedule with Harper.
| Application/Technique | Becca | Harper |
| T-tests and ANOVAs | • | • |
| Correlation & Regression | • | • |
| Mediation, Moderation, and Conditional Process Analysis | • | • |
| Multivariate Models and Path Analysis (Multiple DVs) | • | • |
| Structural Equation Modeling (SEM; estimation of unobserved, latent variables) | • | • |
| Multilevel Modeling for nested data (e.g., repeated measures, participants within groups) | • | • |
| Multilevel SEM | • | |
| Dynamic SEM for intensive longitudinal designs (e.g., daily diary or EMA) | • | |
| Longitudinal SEM | • | |
| Categorical and Count Outcomes | • | |
| Longitudinal Design and Analysis | • | |
| Missing Data Analysis (e.g., FIML, MI) | • | • |
| Power Analysis and Sample Size Planning | • | • |
| Psychometrics and Scale Development | • | |
| Measurement Invariance (to evaluate whether measurement properties hold over time or across groups) | • | |
| Observational Methods (e.g., coding and reliability estimates) | • | • |
| Mixture Models (e.g., latent class analysis) | • | |
| Dyadic Data Analysis (e.g., parent-child, teacher-student, partners) | • | |
| Bayesian Approaches | ||
| Social Network Analysis | ||
| Meta-analysis | ||
| Software Package Note that even if we do not have expertise in the package you are using, we can still provide consultation on model specification and interpretation. | Becca | Harper |
| SPSS | • | • |
| Mplus | • | • |
| HLM | • | • |
| SAS | ||
| R | • | • |
| G*Power | • | • |
How can I prepare to get the most out of my consultation appointment?
A few things to consider prior to the meeting:
- Timeline and Deadlines: Is there a formal deadline (e.g., for a grant or fellowship submission)? By what date do you need the data analysis section completed? It is important to work out a timeline and schedule far in advance given that we often have competing demands for similar deadlines.
- Conceptual Model: What are the primary aims and hypotheses? The more specifics you have worked out prior to the meeting, the better. For example, what are the key variables (IVs and DVs)? Are variables continuous or categorical? Do you have any moderation hypotheses (i.e., for whom or under what conditions effects are present) or mediation hypotheses (i.e., pathways through which effects unfold)? What about statistical controls?
- Design Elements: Do you have multiple measures of a construct? Repeated measures over time? What is a feasible sample size for the project? Are data nested? What about missing data? These details are important for selecting the best analytic approach for your data.
- What to Bring: Ideally, you will bring a diagram/figure with the conceptual model to the meeting. Other materials such as output from prior analytic attempts, syntax/code, etc. are also useful.
Some of these details will be worked out during the consultation; however, thinking through these issues in advance—to the extent possible—will result in a more productive meeting.