visualize_season: visualize trend of pathogen observation rate for NPPCR data...

In oslerinhealth/baker: Bayesian Analysis Kit for Etiology Research

Description

visualize trend of pathogen observation rate for NPPCR data (both cases and controls)

Usage

visualize_season(data_nplcm, patho, slice = 1, slice_SS = 1)

Arguments

data_nplcm	Data set produced by clean_perch_data()
patho	the index of pathogen
slice	the slice of BrS data for visualization; default is 1.
slice_SS	the slice of SS data to add onto BrS plots; default is 1, usually representing blood culture measurements.

Details

This function shows observed positive rate for continuous covariates,e.g., enrollment date in PERCH application. Smoothing is done by penalized splines implemented by mgcv package. The penalized spline smoothing term is constructed by mgcv::smooth.construct.ps.smooth.spec()

Value

A figure with smoothed positive rate and confidence bands for cases and controls, respectively. The right margin shows marginal positive rates.

See Also

Other exploratory data analysis functions: get_top_pattern(), plot_logORmat(), show_individual(), summarize_BrS(), summarize_SS()

oslerinhealth/baker documentation built on May 22, 2021, 12:05 p.m.