rf_summary {graphPAF}

Create a rf.data.frame object

Description

Create a rf.data.frame object for risk factors, prevalence and risk ratios. This will be used in fan plots and nomograms (by simply sending the rf.dat.frame object to plot)

Usage

rf_summary(rf_names, rf_prev, risk, log = FALSE)

Arguments

rf_names

A character vector of risk factor names

rf_prev

A numeric vector specifying prevalence of risk factor in disease controls (estimates of population prevalence can also be used if the disease is rare)

risk

A numeric vector of relative risks or Odds ratios for disease corresponding to each risk factor (if log=FALSE). Log-relative risks or log-odds ratios can be alternatively specified (if log=TRUE)

log

default TRUE. Set to TRUE if relative risks/odds ratios are specified on log-scale

Value

A rf.data.frame object

References

Ferguson, J., O’Leary, N., Maturo, F., Yusuf, S. and O’Donnell, M., 2019. Graphical comparisons of relative disease burden across multiple risk factors. BMC medical research methodology, 19(1), pp.1-9.

Examples

library(ggplot2)
rfs <- rf_summary(rf_names=c('Hypertension','Inactivity','ApoB/ApoA','Diet',
'WHR','Smoking','Cardiac causes','Alcohol','Global Stress','Diabetes'),
rf_prev=c(.474,.837,.669,.67,.67,.224,.049,.277,.144,.129),
risk=c(1.093,0.501,0.428,0.378,0.294,0.513,1.156,0.186,0.301,0.148),log=TRUE)
# fanplot
plot(rfs,fan.point.size=4,fan.label.size=4,
fan.legend.text.size=10,fan.legend.title.size=10,
fan.axis.text.size=10,fan.axis.title.size=10)
# nomogram
plot(rfs,nomogram.label.size=6,
nomogram.axis.text.size=6, type="n")
# reverse nomogram
plot(rfs,nomogram.label.size=6,
nomogram.axis.text.size=6, type="rn")