In this case, a statistical method for longitudinal data must be used. Let us begin with an example: in a randomised controlled trial, we compared two courses of treatment for patients with hip ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Background Coarctation of the aorta (CoA) has good modern results, but large multicentre longitudinal data on outcomes, especially hospital resource utilisation through childhood and adolescence, are ...

We stress that our aim is not to build a longitudinal normative model per se. Considering the much greater availability of cross-sectional data relative to longitudinal data, we instead leverage ...

Nurture-U is a longitudinal survey study conducted at five UK universities, aiming to create a comprehensive data set from over 5000 students. The study will collect data at the start and completion ...

Longitudinal data analysis is most effective when the chosen statistical approach aligns with the frequency of data collection and with the theoretical model underpinning the research question (box 1) ...

Healthcare can change from a reactive to a preventative model by utilizing the power of longitudinal data analysis, providing genuinely personalized care, and enhancing population health overall.

This online course is for anyone who needs to prepare longitudinal data for analysis. It will cover the main procedures needed from converting raw longitudinal data to cleaned data that can be readily ...

Coursera offers a variety of training options for the growing data professional. Explore top data science courses from Coursera now.

Data related to the number of outpatient consultations, history of hospitalization, and the use of multi-agency liaison over the last 5 years, repeatedly measured once every 6 months (i.e., 10-time ...