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Marc
Level II

Concordance analysis with continous variable


           

Hello,

I am trying to solve the following statistical problem in jmp:

1. I got a gold standard fixed variable y (for example: y = 100)

2. I got three data sets x1,x2,x3: (for example x1=92;94;99 / x2=92;94;99;101;103 / x3=92;94;99;101;103;107;100;99;100)
please note: the data sets have similar data, but the number of data points are different. all variables are continuous.


I am looking for with a statistical test or function, to evaluate which dataset x1, x2 or x3 has the closest mean AND the lowest SD to match the gold standard y ? - please note: the gold standard y has no sd, just a fixed value. Looking at ther samples for concordance analysis I just could do this was nominal variables; mine are ordinal or continous.

Any advice much appreciated. Many thanks, Marc
2 ACCEPTED SOLUTIONS

Accepted Solutions

Re: Concordance analysis with continous variable

I understand your use of the word 'concordance' here but that word is also a statistical term that refers to measures of agreement among categorical variables.

I recommend using confidence interval estimates of the mean. The 'gold standard' is your null hypothesis H0: mean = 100) and therefore your alternative hypothesis is that the opposite (H1: mean not = 100). You compare the intervals to the gold standard and to each other using Analyze > Fit Y by X (Oneway platform). Here is your example in a data table laid out for Oneway:

capture.jpeg\\

Here is the Oneway platform with a reference line for the gold standard and the results for ANOVA:

capture.jpeg

Now you compare the confidence interval for each sample. You can plot them in Graph Builder, too. Right-click on the Means for Oneway Anova table and select Make Into Data Table. It might look like this:

capture.jpeg

View solution in original post

Marc
Level II

Re: Concordance analysis with continous variable

4 REPLIES 4

Re: Concordance analysis with continous variable

I understand your use of the word 'concordance' here but that word is also a statistical term that refers to measures of agreement among categorical variables.

I recommend using confidence interval estimates of the mean. The 'gold standard' is your null hypothesis H0: mean = 100) and therefore your alternative hypothesis is that the opposite (H1: mean not = 100). You compare the intervals to the gold standard and to each other using Analyze > Fit Y by X (Oneway platform). Here is your example in a data table laid out for Oneway:

capture.jpeg\\

Here is the Oneway platform with a reference line for the gold standard and the results for ANOVA:

capture.jpeg

Now you compare the confidence interval for each sample. You can plot them in Graph Builder, too. Right-click on the Means for Oneway Anova table and select Make Into Data Table. It might look like this:

capture.jpeg

Marc
Level II

Re: Concordance analysis with continous variable

Many thanks @Mark_Bailey !

txnelson
Super User

Re: Concordance analysis with continous variable

You need to change the "Accepted Solution" from your response to Mark Bailey's response.  The marking of an "Accepted Solution" is not intended to just indicate that a solution to a Discussion Question has been found, but it need to point to the response that has the actual solution

Jim

Re: Concordance analysis with continous variable

hi

do you have any software for solve concordance analysis prpblems?