CuCompare - Software for statistical evaluation for fitted curves

H. A. Kestler and J. M. Kraus

Version from: 2014.02.13

Statistical evaluation and curve fitting of the experimental data

Software for statistical evaluation and curve fitting is available from http://sysbio.uni-ulm.de/soft/CuCompare. The webpage contains source code (R language) and guides through an example workflow. Statistical evaluation is performed by minimizing the least squares deviation of a set of regression functions to the data. The best fitting function is determined by the Akaike information criterion. For statistical comparison of two groups, represented as curves, the sum of the residual sum of squares of the individual regression processes is then compared to that of the regression for the combined data of both groups using the F-test (Motulsky & Ransnas 1987, Lomax & Hahs-Vaughn 2012).

Lomax RG, Hahs-Vaughn DL. Statistical Concepts: A Second Course, Routledge Chapman & Hall, 2012

Motulsky HJ, Ransnas LA. Fitting curves to data using nonlinear regression: a practical and nonmathematical review: The FASEB Journal, 1(5),365-374, 1987

 

Prerequisite: You need actual version of R (http://www.r-project.org/) installed.

Using CuCompare

  1. Download functions.R.
  2. Download process.R.
  3. make a subfolder in the folder you downloaded the two R-files called 'data'.
  4. Download Spa2-Pea2-0.csv into the data folder.
  5. Download Spa2-Pea2-D0.csv into the data folder.
  6. Running the analysis: