The objective for quasi-experimental designs is to establish cause and effect relationships between the dependent and independent variables. However, they have one big challenge in achieving this objective: lack of an established control group.
Membership Webinars
Member Training: Coarsened Exact Matching, an Alternative to Propensity Score Matching
February 29th, 2024 by TAF Support
Member Training: Effective File and Process Management in Statistical Projects
January 31st, 2024 by TAF Support
Member Training: Interactions in Poisson and Logistic Regression – Part 2
December 1st, 2023 by Kim Love
Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions and they become even more difficult to understand. (more…)
Member Training: Frailty Models
November 2nd, 2023 by TAF Support
Most survival analysis models for time-to-event data, like Cox regression, assume independence. The survival time for one individual cannot influence the survival time for another.
This assumption doesn’t hold in many study designs. You may have animals clustered into litters, matched pairs, or patients in a multi-center trial with correlated survival times within a center.
Member Training: Group Comparisons
August 31st, 2023 by guest contributer
How do you know which method to use when you want to compare groups?
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Member Training: Operationalizing Research Questions
July 31st, 2023 by TAF Support
One of the hardest steps in any project is learning to ask the right research question!
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