Concordance analysis with continous variable

Marc

           

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

Mark_Bailey

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:

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

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: