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Making Sense of Analytical Data | LabDataAnalysis.com

A straightforward guide for scientists, engineers, venture capitalists and investors who are generating, interpreting or trying to make sense of analytical data

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PAGE TITLE
Making Sense of Analytical Data | LabDataAnalysis.com | labdataanalysis.com Reviews
<META>
DESCRIPTION
A straightforward guide for scientists, engineers, venture capitalists and investors who are generating, interpreting or trying to make sense of analytical data
<META>
KEYWORDS
1 IVD
2 In vitro diagnostic medical devices
3 Quantitative medical devices
4 Agreement between devices
5 Agreement between methods
6 Specificity of detection
7 Analytical figures of merit
8
9 coupons
10 reviews
CONTENT
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labdataanalysis com,medical devices,specificity of detection,agreement between devices,analytical performance,accuracy/bias,precision,linearity,total analytical error,limit of detection,limit of quantification,interference effects,summary
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Making Sense of Analytical Data | LabDataAnalysis.com | labdataanalysis.com Reviews

https://labdataanalysis.com

A straightforward guide for scientists, engineers, venture capitalists and investors who are generating, interpreting or trying to make sense of analytical data

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1

Linearity of IVD Medical Devices | LabDataAnalysis.com

http://www.labdataanalysis.com/medical_devices/performance4.html

Medical Devices: A Primer for Developers and Investors. A simple linear relationship between the results of a medical device and the true concentration of an analyte is important to health care providers. The assessment of linearity is rather straightforward. The results of the medical device are regressed on the reference values and the regression parameters are evaluated statistically. The following regression models are fitted:. Y = a bX (1). Y = a bX cX. Y = a bX cX. Bias = Y - X (4).

2

Agreement Between Devices - Substantial Equivalence | LabDataAnalysis.com

http://www.labdataanalysis.com/medical_devices/agreement.html

Medical Devices: A Primer for Developers and Investors. The comparison is carried out by analyzing pairs of identical samples using both analytical platforms. There are several ways to look at the data generated by such comparison, but let's start by discussing two wrong, but unfortunately common, ways to analyze data from such comparison studies. As a measure of agreement between the two analytical platforms. Again, you can have a large fixed bias and/or a large proportional bias.

3

Limit of Detection of IVD Medical Devices | LabDataAnalysis.com

http://www.labdataanalysis.com/medical_devices/performance6.html

Medical Devices: A Primer for Developers and Investors. By doing so, we are implying that there is a 5% chance that the analyte will be reported as present (i. e., detected) when it is not present in the sample. This 5% represent the probability of false positive. And is referred to as α. Setting the LoB at the 95th percentile ( α = 0.05) is common, but other values (99th percentile, α = 0.01) may be used. The probability of false negative.

4

Total Analytical Error of IVD Medical Devices | LabDataAnalysis.com

http://www.labdataanalysis.com/medical_devices/performance5.html

Medical Devices: A Primer for Developers and Investors. This is a very important figure of merit that is also quite simple to estimate. In order to calculate the total analytical error, the test results obtained with the device, are compared with the reference values. The errors are estimated for all pairs of results according to:. Error = (Device Test Result) - (Reference Value) (1).

5

Analytical Performance of IVD Medical Devices | LabDataAnalysis.com

http://www.labdataanalysis.com/medical_devices/performance.html

Medical Devices: A Primer for Developers and Investors. In evaluating analytical performance data, it is very helpful to generate plots whenever appropriate and to examine the plots for trends, patterns and any potential human errors. Following is an overview of the assessment of accuracy/bias, precision, linearity, total analytical error, limit of detection, limit of quantification and interference effects.

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Making Sense of Analytical Data | LabDataAnalysis.com

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