13C time series PDR data from normals and three different meals in a cross-over design from the division of Gastroenterology and Hepatology, University Hospital Zurich. See Kuyumcu et al., Gastric secretion does not affect....

Data are formatted as described in usz_13c. In addition, half emptying times from MRI measurements are attached to the data as attribute mri_t50. The example below shows how to analyze the data and present half emptying times from MRI and 13C in diagrams.

data(usz_13c_d)

Examples

library(dplyr) library(ggplot2) data(usz_13c_d) mri_t50 = attr(usz_13c_d, "mri_t50") d = usz_13c_d %>% cleanup_data() %>% # recommended to test for validity nlme_fit() plot(d) + geom_vline(data = mri_t50, aes(xintercept = t50), linetype = 2)
# Maes-Ghoos t50 dd = mri_t50 %>% inner_join( coef(d) %>% filter(parameter=="t50", method == "maes_ghoos"), by = c("patient_id", "group")) %>% mutate( t50_maes_ghoos = value ) ggplot(dd, aes(x=t50, y = t50_maes_ghoos, color = group)) + geom_point() + facet_wrap(~group) + geom_abline(slope = 1, intercept = 0) + xlim(45,205) + ylim(45,205)
#> Warning: Removed 1 rows containing missing values (geom_point).
# Bluck-Coward t50 dd = mri_t50 %>% inner_join( coef(d) %>% filter(parameter=="t50", method == "bluck_coward"), by = c("patient_id", "group")) %>% mutate( t50_bluck_coward = value ) ggplot(dd, aes(x=t50, y = t50_bluck_coward, color = group)) + geom_point() + facet_wrap(~group) + geom_abline(slope = 1, intercept = 0) + xlim(0,205) + ylim(0,205)