Over the last few months, a frequent topic of conversation with my lab mate Donny has been the issue of valid inference following model selection, or model selection bias. This problem has been recognized since at least 1963 and has been written about extensively since then. Some resources I have found both helpful and accessible in understanding model selection bias can be found here, here, and here. However, this issue is still pervasive among social and behavioral scientists,1 so I am writing a short post here in hopes of clarifying the ramifications of drawing inference after selecting a model.