J A Zivin1, D R Waud. 1. Department of Neurosciences, University of California, San Diego, School of Medicine, La Jolla 92093-0624.
Abstract
BACKGROUND: Experimental investigation of stroke, in particular the evaluation of therapeutic maneuvers, is difficult because even well-controlled experiments show considerable variability. Optimal use of resources requires efficient statistical analysis. SUMMARY OF REVIEW: A body of experience in pharmacology that is directly applicable to stroke studies is reviewed. The general approach, though well known to pharmacologists, is less familiar to neurologists. This paper attempts to give a survey so that neurologists encountering studies using this general class of analysis will better be able to put the technique into context. The general nature of a quantal bioassay is described, the underlying conceptual models are discussed, and specific examples are given. CONCLUSIONS: The pharmacologist's approach to the analysis of quantal bioassays can easily be adapted to the quantification of results in studies of stroke.
BACKGROUND: Experimental investigation of stroke, in particular the evaluation of therapeutic maneuvers, is difficult because even well-controlled experiments show considerable variability. Optimal use of resources requires efficient statistical analysis. SUMMARY OF REVIEW: A body of experience in pharmacology that is directly applicable to stroke studies is reviewed. The general approach, though well known to pharmacologists, is less familiar to neurologists. This paper attempts to give a survey so that neurologists encountering studies using this general class of analysis will better be able to put the technique into context. The general nature of a quantal bioassay is described, the underlying conceptual models are discussed, and specific examples are given. CONCLUSIONS: The pharmacologist's approach to the analysis of quantal bioassays can easily be adapted to the quantification of results in studies of stroke.
Authors: William C Culp; Sean D Woods; Aliza T Brown; John D Lowery; Leah J Hennings; Robert D Skinner; Michael J Borrelli; Paula K Roberson Journal: J Neurosci Methods Date: 2012-11-08 Impact factor: 2.390