z2y {AGD}R Documentation

Convert standard deviation scores (SDS) to measurements

Description

Converts standard deviation score (SDS) into measurements using an age- and sex-conditional external reference.

Usage

z2y(z = c(-2, 0, 2), x = 1, sex = "M", sub = "N",
  ref = get("nl4.hgt"), dist = "LMS", dec = 3, sex.fallback = "M",
  sub.fallback = "N")

Arguments

z

A numerical vector containing standard deviation scores that are to be converted. The length length(z) determines the size of the output vector.

x

A vector containing the values of the numerical covariate (typically decimal age or height) at which conversion is desired. Values are replicated to match length(y).

sex

A character vector indicating whether the male ("M") of female ("F")reference should be used. Values are replicated to match length(y).

sub

A character vector indicating the level of the sub field of the reference standard defined in ref

ref

A data frame containing a factor sex, a numerical variable age containing the tabulated decimal point ages, and two or more numerical variables with reference values. See details.

dist

A string identifying the type of distribution. Values values are: "NO", "BCCG", "LMS", "BCPE" and "BCT". The default is "LMS".

dec

A scalar value indicating the number of decimals used to round the value.

sex.fallback

The level of the sex field used when no match is found. The default is "M" for males. Specify sex.fallback="NA" if unmatched entries should receive a NA value.

sub.fallback

The level of the sub field used when no match is found. The default is "N" for normal. Specify sub.fallback="NA" if unmatched entries should receive a NA value.

Details

Functions z2y() and y2z() are the inverse of each other.

The argument dist determines the statistical distribution. The possibilities are as follows:

list("\"NO\"")

ref should contain columns mean and sd, containing the mean and the standard deviation in the external reference population.

list("\"LMS\"")

ref should contain columns L, S and M containing the LMS parameters.

list("\"BCCG\"")

ref should contain columns mu, sigma and nu containing the Box-Cox Cole-Green parameters.

list("\"BCPE\"")

ref should contain columns mu, sigma, nu and tau containing the Box-Cox Power Exponential parameters.

list("\"BCT\"")

ref should contain columns mu, sigma, nu and tau containing the Box-Cox T distribution parameters.

Value

For y2z(): A vector with length(y) elements containing the standard deviation score. For z2y(): A vector with length(z) elements containing quantiles.

Author(s)

Stef van Buuren, 2010

See Also

y2z

Examples

boys <- boys7482

# quantile at SD=0 of age 2 years,
# height Dutch boys
z2y(z=0, x=2)

# same for Dutch girls
z2y(z=0, x=2, sex="F")

# quantile at SD=c(-1,0,1) of age 2 years, BMI Dutch boys
z2y(z=c(-1,0,+1), x=2, ref=nl4.bmi)

# 0SD line (P50) in kg of weight for age in 5-10 year, Dutch boys
z2y(z=rep(0,6), x=5:10, ref=nl4.wgt)

# 95th percentile (P95), age 10 years, wfa, Dutch boys
z2y(z=qnorm(0.95), x=10, ref=nl4.wgt)

# table of P3, P10, P50, P90, P97 of weight for 5-10 year old dutch boys
# age per year
age <- 5:10
p <- c(0.03,0.1,0.5,0.9,0.97)
z <- rep(qnorm(p), length(age))
x <- rep(age, each=length(p))
w <- matrix(z2y(z, x=x, sex="M", ref=nl4.wgt), ncol=length(p),
 byrow=TRUE)
dimnames(w) <- list(age, p)
round(w,1)

# standard set of Z-scores of weight for all tabulated ages, boys & girls
# and three etnicities
sds <- c(-2.5, -2, -1, 0, 1, 2, 2.5)
age <- nl4.wgt$x
z <- rep(sds, times=length(age))
x <- rep(age, each=length(sds))
sex <- rep(c("M","F"), each=length(z)/2)
w <- z2y(z=z, x=x, sex=sex, ref=nl4.wgt)
w <- matrix(w, ncol=length(sds), byrow=TRUE)
dimnames(w) <- list(age, sds)
data.frame(sub=nl4.wgt$sub,sex=nl4.wgt$sex,round(w,2), row.names=NULL)

# P85 of BMI in 5-8 year old Dutch boys and girls
e <- expand.grid(age=5:8, sex=c("M","F"))
w <- z2y(z=rep(qnorm(0.85),nrow(e)), x=e$age, sex=e$sex, ref=nl4.bmi)
w <- matrix(w, nrow=2, byrow=TRUE)
dimnames(w) <- list(c("boys","girls"),5:8)
w

# data transformation of height z-scores to cm-scale
z <- c(-1.83, 0.09, 2.33, 0.81, -1.20)
x <- c(8.33,  0.23, 19.2, 24.3, 10)
sex <- c("M", "M", "F", "M", "F")
round(z2y(z=z, x=x, sex=sex, ref=nl4.hgt), 1)

# interpolate published height standard
# to daily values, days 0-31, boys
# on centiles -2SD, 0SD and +2SD
days <- 0:31
sds  <- c(-2, 0, +2)
z    <- rep(sds, length(days))
x    <- rep(round(days/365.25,4), each=length(sds))
w    <- z2y(z, x, sex="M", ref=nl4.hgt)
w    <- matrix(w, ncol=length(sds), byrow=TRUE)
dimnames(w) <- list(days, sds)
w
[Package AGD version 0.35 Index]