Applying the Right Statistics: Analyses of Measurement Studies

I have been learning a great deal about statistical analysis, and how to apply the abundant tools to particular problems… I  guess I should say that I will be sharing some articles and ideas that I have come across on this topic (there are a number of considerations for every question.  Bazsinga).  BTW; I have been using SOFA Statistics (link later, free for use, has “enhancers” you can pay for, but don’t need to before using it to the full potential) for my own bit of work, it is really nice, sometimes frustrating tool, though I am fairly sure that has more to do with my “not knowing what I can do”, rather than limitations in the software.

 

Introduction

Many research papers in radiology concern measurement. This is a topic which in the past has been much neglected in the medical research methods literature. When I was first approached with a question on measurement error, I turned in vain to my books. I had to work it out myself.

I am going to deal in this talk with two types of study: the estimation of the agreement between two methods of measurement, and the estimation of the agreement between two measurements by the same method, also called repeatability. In both cases I shall be concerned with the question of interpreting the individual clinical measurement. For agreement between two different methods of measurement, I shall be asking whether we can use measurements by these two methods interchangeably, i.e. can we ignore the method by which the measurement was made. For two measurements by the same method, I shall be asking how variable can measurements on a patient be if the true value of the quantity does not change and what this measurement tells us about the patient’s true or average value.

I shall avoid all mathematics, which even an audience as intelligent as this one finds difficult to follow during a presentation, except for one formula near the end, for which I shall apologise when the time comes. Instead I shall show what happens when we apply some simple statistical methods to a set of randomly generated data, and then show how this informs the interpretation of these methods when they are used to tackle measurement problems in the radiology literature.

For an example of the sort of study with which I shall be concerned, Borg et al. (1995) compared single X-ray absorptiometry (SXA) with single photon absorptiometry (SPA). They produced the following scatter plot for arm bone mineral density:

via Applying the Right Statistics: Analyses of Measurement Studies.

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