I have tried various approaches such as Bland Altman plots, Linn's Correlation Coefficient, paired T tests etc. The only thing I had not yet succeeded in is getting the each measure using each device to be represented by one single value which takes into account the serial measures. All devices are measuring the same thing : mean arterial pressure in mmHg. The gold standard is a radial arterial catheter which directly measures the pressures at the wrist. Blood pressure cuffs were placed on the upper arm, lower arm, and calf, but the Mean arterial pressure is oscillometric, based on the pressure at which maximum fuctuations are sensed. The device that the trial was on is a fingertip device that measures pulsations. An algorithm based on trials of this compared to an arterial line reads out the pressures. I had really great and meaningful results with the concordance coefficient, but the relationship wasn't meaningfully consistent across each sampling time, so thats why I thought I could get something more meaningful if Included data from all time points into a model. residuals are normally distributed in all the measures. Untimately , the goal of the project is to determine whether any of the cuff measures or device is close enough to the arterial line to be clinically valid. The reason for this is that the population under study is not a normal, healthy sample of the general population.
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