Package index • serodynamics

Simulate case data

sim_case_data(): Simulate longitudinal case follow-up data from a homogeneous population

Prepare data for analysis

serodynamics_example(): Get path to an example file
load_data(): load and format data
as_case_data(): Convert data into case_data
prep_data(): prepare data for JAGs

Visualize data

autoplot(<case_data>): Plot case data

Prepare auxiliary JAGS inputs

prep_priors(): Prepare priors
initsfunction(): JAGS chain initialization function

Model seroreponse

run_mod(): Run Jags Model

Model diagnostics

plot_jags_dens(): Density Plot Diagnostics
plot_jags_Rhat(): Rhat Plot Diagnostics
plot_jags_trace(): Trace Plot Diagnostics
plot_jags_effect(): Plot Effective Sample Size Diagnostics
plot_predicted_curve(): Generate Predicted Antibody Response Curves (Median + 95% CI)

Postprocess JAGS output

postprocess_jags_output(): Postprocess JAGS output

Summarize seroresponse model estimates

post_summ(): Summary Table of Jags Posterior Estimates

Model 2a: cross-biomarker extension (Chapter 2)

Chapter 2 extension that adds a same-parameter cross-biomarker covariance to the Chapter 1 model via a shared latent factor (strictly nests Chapter 1).

run_mod_2a(): Fit Model 2a (Chapter 1 + alpha) with JAGS
compare_mod_2a(): Compare Chapter 1 and Model 2a on the same data
fit_chapter1_lean(): Lean Chapter 1 fit (for comparison with Model 2a)
summarize_cross_2a(): Summarize cross-biomarker covariance from a Model 2a fit
summarize_curve_params_2a(): Summarize shared curve-parameter posteriors
validate_recovery_2a(): Validate Model 2a parameter recovery
validate_nesting_2a(): Validate the Chapter 1 nesting / no-false-positive behaviour
sim_case_data_2a(): Simulate longitudinal case data with known cross-biomarker covariance
sim_params_2a(): Simulate subject-level parameters with a known Model 2a covariance
prep_priors_2a(): Prepare priors for Model 2a
add_factor_priors(): Append Model 2a factor priors to a Chapter 1 prior list
jags_data_2a(): Build the combined JAGS input list for Model 2a
make_inits_2a(): Initial-value factory for Model 2a chains
build_sigma_2a(): Assemble a Model 2a covariance matrix
cross_cov_from_loadings(): Convert factor loadings to cross-biomarker covariance
cross_cor_from_draw_2a(): Convert loadings + precisions to cross-biomarker correlation
marginal_var_2a(): Marginal within-biomarker variance under the factor model

Example data sets

serodynamics_example(): Get path to an example file
nepal_sees: SEES Typhoid data
nepal_sees_jags_output: SEES Typhoid run_mod jags output