File Exchange > Data Analysis >    Compare Linear Fit Parameters and Datasets

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Compare datasets using a linear model, or compare intercept and slope.

Screen Shot and Video:

This app can be used to:

  • Compare slope and intercept across multiple datasets.
  • Compare multiple datasets using a linear model.

Download the file "Compare Linear Fit Parameters and Datasets.opx", and then drag-and-drop onto the Origin workspace. A "Compare Linear Fit Parameters and Datasets" icon will appear in Origin's Apps panel.


  1. With a worksheet or graph active, click the "Compare Linear Fit Parameters and Datasets" icon from the Apps panel to open the dialog. The Settings node provides option for comparing datasets or comparing parameters. This node also provides two options for method: Akaike Information Criteria(AIC) and F-test. If there are more than 2 datasets, it allows to compare datasets pairwise if there is difference among all datasets.
  2. When the dialog is open, click the ? button on the top-right corner, or press F1 to open the help file, which includes explanation of the dialog settings and an example.


v1.2: Fix bug of wrong column lable in report parameter table
v1.1: Add option for pairwise comparison

Reviews and Comments:
09/20/2023OriginLabHi, sto5087

Please note that you can find the detailed information in the help file of the app (Press F1 when the dialog is opened). In the Algorithm part there is details how the F-test works and makes conclusion.

09/19/2023sto5087How does the F-test determine whether the slopes are statistically different? Does the F-value need to be below some value to show they are different? Any information about this is much appreciated.

05/10/2022JMW6821could you use this test for non linear parameters like a 4 or 5pL curve?

04/11/2022OriginLabHi borosemil,

This app compares datasets/parameters by comparing two models: a model to combine two or more datasets (concatenate) and fit the combined data with the same model, another model to fit two or more datasets separately. Then compare whether a model is significantly better than another by AIC or F-test. If yes, we can conclude datasets are significantly different.

04/11/2022borosemilI don't understand how to interpret the result of 'same and different' AIC and Akaike weight results? As far as I know Akaike coefficient is a single ordering value of the compared models. Can somebody help me?

05/24/2020OriginLabHi DeAn Wei,
Please make sure that you are running Origin 2016 or later version, and you have upgraded the app to its latest version (v1.1). Also, I wonder if you saw any error messages when you click the app icon? If yes, please contact us via
OriginLab Tech Support

05/23/2020DeAn Wei打不开啊

09/13/2019chechar2020MUY VERSATIL

04/14/2017mario19810312Very usefull