Monte Carlo simulation of parameter confidence intervals for non-linearregression analysis of biological data using Microsoft Excel.

摘要

This study describes a method to obtain parameter confidence intervals from thefitting of non-linear functions to experimental data, using the SOLVER andAnalysis ToolPaK Add-In of the Microsoft Excel spreadsheet. Previously we haveshown that Excel can fit complex multiple functions to biological data,obtaining values equivalent to those returned by more specialized statistical ormathematical software. However, a disadvantage of using the Excel method was theinability to return confidence intervals for the computed parameters or thecorrelations between them. Using a simple Monte-Carlo procedure within the Excelspreadsheet (without recourse to programming), SOLVER can provide parameterestimates (up to 200 at a time) for multiple 'virtual' data sets, from which therequired confidence intervals and correlation coefficients can be obtained. Thegeneral utility of the method is exemplified by applying it to the analysis ofthe growth of Listeria monocytogenes, the growth inhibition of Pseudomonasaeruginosa by chlorhexidine and the further analysis of the electrophysiologicaldata from the compound action potential of the rodent optic nerve.