The daz() function calculated the "Development for Age Z-score". The DAZ represents a child's D-score after adjusting for age by an external age-conditional reference. The zad() is the inverse of daz(): Given age and the Z-score, it finds the raw D-score.

daz(d, x, reference = get_reference(), dec = 3)

zad(z, x, reference = get_reference(), dec = 2)

## Arguments

d

Vector of D-scores

x

Vector of ages (decimal age)

reference

A data.frame with the LMS reference values. The default uses the get_reference() function. This selects a subset of rows from the builtin_references.

dec

The number of decimals (default dec = 3).

z

Vector of standard deviation scores (DAZ)

## Value

Unnamed numeric vector with Z-scores of length length(d).

Unnamed numeric vector with D-scores of length length(z).

## Details

Note 1: The Box-Cox Cole and Green (BCCG) and Box-Cox t (BCT) distributions model only positive D-score values. To increase robustness, the daz() and zad() functions will round up any D-scores lower than 1.0 to 1.0.

Note 2: The daz() and zad() function call modified version of the pBCT() and qBCT() functions from gamlss for better handling of NA's and rounding.

dscore()

## Author

Stef van Buuren 2020

## Examples

# using GSED Phase 1 reference
daz(d = c(35, 50), x = c(0.5, 1.0))
#>  0.788 0.587

# using Dutch reference
daz(d = c(35, 50), x = c(0.5, 1.0), reference = get_reference("gcdg"))
#>  -0.425  0.299

# using Dutch reference
daz(d = c(35, 50), x = c(0.5, 1.0), reference = get_reference("dutch"))
#>  -0.091  0.357
# population median at ages 0.5, 1 and 2 years, phase1 reference
zad(z = rep(0, 3), x = c(0.5, 1, 2))
#>  32.28 47.93 64.30

# population median at ages 0.5, 1 and 2 years, gcdg reference
zad(z = rep(0, 3), x = c(0.5, 1, 2), reference = get_reference("gcdg"))
#>  36.32 49.11 62.67

# population median at ages 0.5, 1 and 2 years, dutch reference
zad(z = rep(0, 3), x = c(0.5, 1, 2), reference = get_reference("dutch"))
#>  35.27 48.91 63.77

# percentiles of D-score reference
g <- expand.grid(age = seq(0.1, 2, 0.1), p = c(0.1, 0.5, 0.9))
d <- zad(z = qnorm(g$p), x = g$age)
matplot(
x = matrix(g\$age, ncol = 3), y = matrix(d, ncol = 3), type = "l",
lty = 1, col = "blue", xlab = "Age (years)", ylab = "D-score"
) 