About: logit-log curve fitting   Goto Sponge  NotDistinct  Permalink

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AttributesValues
type
label
  • logit-log curve fitting
subClassOf
described by
term editor
  • James Malone
  • Melanie Courtot
  • Elisabetta Manduchi
  • Ryan Brinkman
example of usage
  • Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution. In this case OD_0 (also referred to OD_min) and OD_infty (also referred to OD_max) correspond to the theoretical OD of the assay at zero and infinite concentrations, respectively.
definition
  • A logit-log curve fitting is a curve fitting where first the limits y_0 an y_infty of y when x->0 and x->infinity, respectively, are estimated from the input data points (x_1, y_1), (x_2,y_2), ..., (x_n, y_n). Then a curve with equation log((y-y_0)/(y_infty-y))=a+b log(x) is obtained, where a and b are determined to optimize its fit to the input data points.
definition source
  • ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1448
editor preferred term
  • logit-log curve fitting
has curation status
editor note
  • The above definition refers to the 'fully specified' logit-log model. The reduced form of this, when it is assumed that y_0=0, is named 'partially specified' logit-log model.
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