A frequent problem in estimating logistic regression models is a failure of the likelihood maximization algorithm to converge. In most cases, this failure is a consequence of data patterns known as complete or quasi-complete separation. For these patterns, the maximum likelihood estimates simply do not exist. In this paper, I examine how and why complete or quasi-complete separation occur, and the effects they produce in output from SAS ® procedures.I then describe and evaluate several possible solutions.
Shaken baby syndrome is evaluated in the context of its historical evolution and its veracity in referring to causal injury mechanisms. A rational assessment of the injury causation and consequent pathological states associated with the syndrome is presented. It is now evident that shaken baby syndrome evolved as a result of a faulty application of scientific reasoning and a lack of appreciation of mechanisms of injury. A brief explanation of the commonly understood usage and interface of scientific methodology and reasoning as applied to clinical medicine is given.
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