Back-PredicteR is an application which helps you to back-predict responses to results when the relation between the response and the result is known. A typical example is when performing an assay in a laboratory. You want to determine the concentration of unknown samples. For that, you have first to determine the relation between the response of your assay (absorbance, fluorescence, ...) and the concentration of your sample (result) by measuring the response of your assay for samples of known concentration (calibration data).
Steps:
  1. Load data or load a test data sample
  2. Choose your model(s)
  3. Check your results
  4. Download your results

Load data

Upload a file :
Download a template or an example.

Release: 1.0 | Last Update: April 07 2017 | Copyright: Pharmalex 2001-2017.
Head calibration data:

              
            
Head data to back predict:

              
            

Linear regression:



Weighted (1/X) linear regression:



Weighted (1/X^2) linear regression:



Linear regression after (base 10) LOGARITHM transformation of both concentration and response:



Linear regression after SQUARE ROOT transformation of both concentration and response:



Quadratic regression:



Weighted (1/X) quadratic regression:



Weighted (1/X^2) quadratic regression:



Four parameters logistic Regression:



Weighted (POM) Four parameters logistic Regression:



Five parameters logistic Regression:



Weighted (POM) Five parameters logistic Regression:



Power Regression:



Weighted (POM) Power Regression: