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…)
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…)
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.
How do you know which method to use when you want to compare groups?
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Many data sets are challenging and time consuming to work with because the data are seldom in an optimal format.
Moderated mediation, also known as Conditional Process Modeling, is great tool for understanding one type of complex relationship among variables.