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# vitdcurves is output from vitd.curve
# expos is output from exposure levels
# infect is output from infection.count
rr.profile.plot <- function( x, expos, infect, idx = 1, ... )
{
vitdcurves <- x
if( !inherits( vitdcurves, "vitd.curve" ) ) stop("Argument 'vitdcurves' not of class 'vitd.curve'")
if( !inherits( expos, "exposure.levels" ) ) stop("Argument 'expos' not of class 'exposure.levels'")
if( !inherits( infect, "infection.count" ) ) stop("Argument 'infect' not of class 'infection.count'")
if( length(idx) > 1 ) warning("Length of idx is greater than 1: only first element used")
idx <- idx[1]
par( mfrow = c(1,2) )
m <- 12*vitdcurves$res + 1 # take one yr
time <- ( vitdcurves$time[1:m] ) / ( 12 / pi )
h <- max( vitdcurves$curve$curves.eval[idx,] ) + 10
# plot vit d profile for single participant
plot( time, vitdcurves$curve$curves.eval[ idx, 1:m] , type = "l", xlab = "Time",
ylab = "25 Hydroxy Vitamin D", ylim = c(0, h), axes = FALSE )
axis( 2, ... )
months <- c( month.abb[3:12], month.abb[1:3] )
axis( 1, at = seq( time[1], time[length(time)], length.out = 13 ), labels = months, ... )
year <- max( which(expos$exposures[ idx, ] < pi) )
points( expos$exposures[idx, 1:year], expos$levels[idx,1:year], col = "blue", cex=1.3, ... )
index <- which( infect$infection[idx,1:year] == 1 )
points( expos$exposures[idx, index], expos$levels[idx,index], pch = 20, cex = 1.5, col = "red" )
# plot relative risk curve
lvl <- seq( 0, h - 10 , 1 )
lower <- infect$baseline
upper <- lower * infect$RR
lo <- infect$inflection[1]
hi <- infect$inflection[2]
tau <- 0.045*(hi-lo) # tau to control inflection points
slope <- log( (hi-lo-tau)^2/tau^2 ) / (hi-lo)
intercept <- log( (hi-lo-tau)/tau ) - slope * hi
OR.curve <- glf( lvl, lower, upper, intercept, slope )
plot( OR.curve, lvl, type = "l",
xlab="Relative Risk", ylab="", ylim=c(0, h), axes = FALSE, ... )
axis( 1, at = seq( lower, upper, length.out = 6 ), labels = seq( 1, infect$RR, length.out = 6 ) )
points( infect$probs[idx,1:year], expos$levels[idx,1:year], cex = 1.3, col = "blue" )
points( infect$probs[idx,index], expos$levels[idx,index], type = "p", pch = 20, cex = 1.5, col = "red" )
par( mfrow = c(1,1) )
}
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