An brief introduction to the cosinor model | Introduction | cglmm() | A basic overview of cglmm() | Understanding the output | More advanced cglmm() model specification | Using summary() and testing for differences between estimates | Using predict() | Plotting cglmm objects | Large datasets | Assessing residual diagnostics of cglmm regression models using DHARMa | Differential rhythmicity | References

cglmm() | Using cglmm() | Specifying a single-component model with no grouping variable | Specifying a single-component model with a grouping variable and a shared MESOR | Specifying a single-component model with a grouping variable and an intercept (MESOR) | Specifying more complicated models using the amp_acro() function | Dispersion and zero-inflation model specification | Using summary(cglmm)

Visualizing cglmm models | Polar plots

Data with subject-level differences | A single component model with random effects | REML

Generating a two-component model | Generating a three-component model | Generating models with n-components

Simulating rhythmic data | Understanding the inputs for a simple model | Simulating grouped cosinor data | Simulating multi-component cosinor data

Updates since the initial release (circacompare 0.1.0) and Bioinformatics journal article. | Introduction to circacompare, using fixed-effects only models and no customized model parametrization | Input data | circa_single() | circacompare() | When to use what | Mixed-model variants and how to customize the parameterization of the model | Firstly, a mention on control and model parameters | Examples | Period and decay parameters | Limitations | Decay functions | Period and phase parameters | Model diagnostics and choice

Introduction | What's being simulated? | Example function | do_nmb_sim() | screen_simulation_inputs() | References

Making plots with predictNMB | Plotting the results from screen_simulation_inputs() | Choosing the x-axis variable and other constants | Choosing a y-axis variable | Selecting what to show on the plot | Other plot modifications | Plotting the results from do_nmb_sim() | autoplot() | ce_plot() | Making tables with predictNMB | References

NMB functions | Key considerations | Making functions by hand | Making functions using get_nmb_sampler() | Tracking QALYs | Passing these functions to do_nmb_sim()

Detailed example | Model inputs | References