2
$\begingroup$

I'm interested in developing a model for the circadian rhythm of hormone levels via a cosinor analysis. I just started looking into cosinor analyses so I have a few questions.

The data is being collected at the moment, but I'm trying to get a better understanding of the method before the actual data arrives. This is how the data should look like: a total of 12 subjects with each subjects' hormone levels measured every 30 minutes over a period of 6 days. On days 1-3 subjects were administered drug A and on days 4-6 drug B. A 24 hour cycle is expected and therefore I'm interested in developing a model for a 24h circadian rhythm for each of the two drugs. This means I have multiple cycles - 24hours each - per person for each of the two drugs.

After reading the following two reviews (Fernandez et al., 2009; Cornelissen 2014) on cosinor it seems that I want to perform a population-mean cosinor analysis. Assuming that the necessary assumptions are met and in the simplest case of a single-component cosinor, I'm wondering how I would go ahead and do the analysis.

My understanding is that I should first calculate a single-component cosinor for each subject and then average the parameter estimates to get the population mean estimates. Say for drug A, can I simply combine the first three days of data for each subject to compute the single-component cosinors? Once I have those 12 single-component cosinors can I then just average them to get the population mean estimates? Do I have to account for the fact that I have repeated cycles for each subject, for example in the computation of variance estimates?

$\endgroup$

1 Answer 1

0
$\begingroup$

The way I understand the cosinor is that it can and is recommended to be performed over several cycles. The reason is Nyquist frequency i.e. you can reliably detect a frequency with at least 2 cycles of it and the more cycles you have, the better estimation you get (assuming stationary rhythm). In your case I would definitely perform single cosinor analyses for every subject and treatment. The problem here is repeated measures. As cosinor is a special case of linear regression, it probably can be combined with linear mixed model approach. Although I have not read them myself but these references could probably help:

Mikulich SK, Zerbe GO, Jones RH, Crowley TJ. Comparing linear and nonlinear mixed model approaches to cosinor analysis.

Weaver, Royal John Analysis of rhythmic biological data: The mixed-effects cosinor model.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.