What statistical test should I use to investigate how changes in variables A (continuous; defined as A at Time2- A at Time1) affect changes in Variables B (continuous; defined as B at Time2 - B at Time1) using longitudinal data? I really appreciate your help.
Hi,
Repeated measure analysis. Here are a few references:
https://www.sciencedirect.com/topics/mathematics/repeated-measure-analysis
Schober P, Vetter TR. Repeated Measures Designs and Analysis of Longitudinal Data: If at First You Do Not Succeed-Try, Try Again. Anesth Analg. 2018;127(2):569-575. doi:10.1213/ANE.0000000000003511
https://online.stat.psu.edu/stat510/lesson/10/10.1
For atheoretical insight try: Get this book in print
M. Ataharul Islam, Rafiqul I Chowdhury.Analysis of Repeated Measures Data. Publisher-Springer Singapore, Year: 2017
ISBN: 978-981-10-3793-1, 978-981-10-3794-8
Also, this one is a good practical book:
Repeated Measures Design for Empirical Researchers
J. P. Verma, Wiley
ISBN: 978-1-119-05271-5
It depends if you only wish to assess weather the difference between A and B at a given (i,j) point is significant. In that case, a repeated measure t test would be sufficient. I dont think you need ANOVA given you are only testing between time(i) and time (j), and not multiple time events. If you wish to assess the manner by which both A and B vary simultaniously across time, and their relation together, then I would recommend using linear regression analysis. First calculate the difference for A and B seperately for any given (i-j) times (time1-time2, time 2-time 3, etc..) and then you are left with 2 columns of data that match each other- A(i,j) and B(i,j) for any given time difference. You simply run a linear regression analysis for these 2 coumns of continous data.
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