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- Method Comparison

May 28, 2014 3:49 AM

This add-in helps you compare measurement methods according to CLSI guidelines. It calls various JMP platforms behind the scenes to fit the data and create a variety of graphical and tabular results.

The add-in consists of four primary routines: Accuracy, Precision, Linearity, and Performance. The input data table to each of them must be in stacked format, that is, with one row per individual response. One column must identify the different rows of data corresponding to the different methods used (the Method Identifer column). Other required columns of data depend on the routine you use.

To install the add-in, download "Method Comparison.jmpaddin", drag it onto an open JMP window, then click "Install".

For example analyses, click Add-Ins > Method Comparison > Help after installing the add-in. The add-in also includes four example data sets: "Compound Comparison", "Peak Expiratory Flow Rate", "Simulated Example", and "Systolic Blood Pressure". Click Add-Ins > Method Comparison > Example Data to open them.

Some example screen shots are below.

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01-24-2017
04:21 AM

Hi,

thanks for the add-in for method comparison. I have a question/remark regarding the Bland Altman plot: why is using the Std Error and not the Std Deviation (SD) to calculate the 95% limits of agreement? The use of Std Error is wrong and consequently is giving wrong limits of agreement.

Literature about Bland Altman plot and the use of Std Deviation (SD):

1. Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res 1999;8:135-60

2. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Int J Nurs Stud 2010;47:931-6

3.Giavarina D. Understanding Bland Altman analysis. *Biochemia Medica*. 2015;25(2):141-151

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03-24-2017
08:10 AM

Hi,

What method are you using for the Confidence Intervals for the Passing Bablock intercept and slope? If it is bootstrap then please specify what type (e.g., 2.5th and 97th percentile of the distribution of the predicted Y from all the bootstrap estimates) or something else.

Thanks,

David

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08-24-2017
07:53 PM

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10-17-2017
12:26 PM

@sstinca Apologies for the very long delay. When we switched over to the new JMP Community website somehow I never got notified of your message. Thanks for the great catch and I just uploaded an update that includes the Bland-Altman limits using standard deviation and a shaded display on the Matched Pairs graph. Also added the Systolic Blood Pressure data example from their 1999 paper and numbers agree.

@dstokar The limits are based on the original SAS Macro code from Roche in Penzberg, Germany, which implement the method from Passing and Bablok (1983) and do not use the bootstrap. If you have good evidence the bootstrap works well here please share, and also the JSL code is open so you can see exactly what is going on and modify it as desired.

@juanpahn Suggest working through the example in the help doc, making sure you understand everything, then try it on your own data.

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01-24-2018
12:20 AM

I am using the ‘Method Comparison’ Add-In developed by Russ Wolfinger to compare different methods to analyze ovaries using 2D and 3D ultrasound. I have two questions:

- The Deming Regression provides the confidence interval for the slope to evaluate proportional bias, but a confidence interval is not provided in the output for the intercept. I understand that we can evaluate systematic bias from the mean difference output provided underneath the Bland Altman graphs, but for completeness in our results, it would be helpful to have the CI for the intercept of the Deming Regression as well. Can this be included in the input and/or how do you recommend I ascertain the confidence interval around the intercept?
- I am uncertain what the black diamond/ lines around the periphery of the Bland Altman graphs are – it’s not clarified in the ‘Help’ section and not described by Bland Altman’s original publication. Is it possible to clarify what these lines represent?

Many thanks.

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05-04-2018
05:07 PM

Hi Russ,

Stupid question probably, but I'll ask still...

I went through the tutorial with the example you give in the attached word document and it worked perfectly just like in your example but then when I tried with my data, I got totally confused.

I just would like to have a Passing-Bablok regression analysis done. I just need to have and equation to my curve and a correlation coefficient. My data is like the table below.

specimen | method1 | method2 | method3 |

S1 | 0.322613947 | 0.283500366 | 0.394930806 |

S2 | 1.836453685 | 1.666623257 | 1.081888255 |

S3 | 3.276624674 | 3.338295056 | 1.384727721 |

S4 | 4.718858377 | 4.697249324 | 1.58673576 |

S5 | 0.318644745 | 0.311580094 | 0.272826006 |

S6 | 1.880639096 | 1.957200801 | 0.929268173 |

S7 | 3.390383424 | 3.417362369 | 1.28341812 |

S8 | 4.564628617 | 4.394208312 | 1.527136804 |

S9 | 0.343720425 | 0.424129692 | 0.912531427 |

S10 | 2.187688239 | 2.413766417 | 0.20302838 |

S11 | 3.402107778 | 3.153607989 | 1.277589378 |

S12 | 5.273795942 | 5.300136478 | 1.838240998 |

S13 | 0.67104692 | 0.414658177 | 0.432221887 |

S14 | 2.085992847 | 1.965456038 | 0.940358883 |

S15 | 3.712645639 | 4.047605658 | 1.189165635 |

S16 | 4.987225862 | 4.857789074 | 1.424112418 |

S17 | 0.298670082 | -0.114521527 | 0.449896278 |

S18 | 1.875760383 | 1.8653793 | 0.918795834 |

S19 | 3.703566214 | 3.642433157 | 1.112434596 |

I thought maybe I needed a table like the one below and put the first column as "method identifier" and the second column in "X, concentration" or "Y, response" but then, what do I put in X or Y?

measure | |

method1 | 0.322614 |

method1 | 1.836454 |

method1 | 3.276625 |

method1 | 4.718858 |

method1 | 0.318645 |

method1 | 1.880639 |

method2 | 3.390383 |

method2 | 4.564629 |

method2 | 0.34372 |

method2 | 2.187688 |

method2 | 3.402108 |

method2 | 5.273796 |

In the compound comparison tutorial, I don't understand what is "method identifier" and what I am supposed to put here. I guess "X, concentration" corresponds to the reference method measures and "Y, response" corresponds to the new method measures but I am not even sure of that. Any way to help? Thanks a lot

--Pierre

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05-04-2018
05:29 PM

@Heidi_V, yikes, sorry for the long delay! There is a request in to R&D get that confidence interval on the intercept printed in JMP's Orthogonal Regression platform. Thanks for the request and please feel free to keep bugging us about it, or if you are feeling bold I don't think the calculations are too bad given what the add-in already produces. For the diamonds in the Matched Pairs platform, see page 248 of https://www.jmp.com/support/downloads/pdf/jmp9/basic_analysis_and_graphing.pdf

@Pierre, you are on the right track with stacking your data. Your first new column is the method identifier and the second one is Y. You're going to need add an X column somehow; ideally from the experiment itself or if you just don't have it I think using sequential integers (starting over within each method) should work. The examples from the add-in are good to study.

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06-11-2018
04:09 PM

Russ,

Looking at some data and comparing to manual calculations done in excel and matlab it seems that JMP calculates the LOA as the std deviation of differences * 1.96. However the Bland-Atlman paper from 1986 calls for using a corrected standard deviation when repeated measures are used that is *sc = [S**D^*2 + .25 (*s1)^*2 + .25 (*s*2)^2]^5

Is there a way to run the accuracy add-in that allows for repeated measures?

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