extractLMS: Extracts LMS values from a gamlss object.

In AGD: Analysis of Growth Data

Extracts LMS values from a gamlss object.

Description

Extract LMS values from a gamlss object for solutions that transform the age axis according to the M-curve.

Usage

extractLMS(
  fit,
  data,
  sex = "M",
  grid = "classic",
  decimals = c(4, 4, 4),
  flatAge = NULL
)

Arguments

fit	A gamlss object containing the final fit on transformed age, t.age.
data	A data frame containing the original data, with both age and t.age
sex	A character vector indicating whether the fit applied to males sex="M" or females sex="F". The default is sex="M".
grid	A character vector indicating the desired age grid. See ageGrid() for possible options. The default is a grid="classic", a grid of 59 age points.
decimals	A numerical vector of length 3 indicating the number of significant digits for rounding of the L, M and S curves, respectively.
flatAge	A scalar indicating the age beyond which the L, M and S values should be constant. The default (NULL) is not to flatten the curves.

Details

It is crucial that t.age in data correspond to exactly the same age transformation as used to fit the gamlss object. Age grid values beyond the range of data$age produce NA in the L, M and S values. Parameter flatAge should be one of the values of the age grid.

Value

A data frame with rows corresponding to time points, and with the following columns: sex,x,L,M,S.

Author(s)

Stef van Buuren, 2010

Examples

## Not run: 
#
library(gamlss)
boys <- boys7482

# calculate initial M curve
data <- na.omit(boys[,1:2])
f0154  <- gamlss(hgt~cs(age,df=15,c.spar=c(-1.5,2.5)),
                sigma.formula=~cs(age,df=4,c.spar=c(-1.5,2.5)),
                data=data,family=NO,
                control=gamlss.control(n.cyc=3))                      

# calculate transformed age
t.age <- fitted(lm(data$age~fitted(f0154)))
t.age <- t.age - min(t.age)
data.t <- data.frame(data,t.age=t.age)

# calculate final solution
f0106r <- gamlss(hgt~cs(t.age,df=10,c.spar=c(-1.5,2.5)),
                sigma.formula=~cs(t.age,df=6,c.spar=c(-1.5,2.5)),
                data=data.t,family=NO,
                control=gamlss.control(n.cyc=3))

# extract the LMS reference table in the 'classic' age grid
nl4.hgt.boys <- extractLMS(fit = f0106r, data=data.t, grid="compact", 
               dec = c(0,2,5))
nl4.hgt.boys


# flatten the reference beyond age 20Y (not very useful in this data)
nl4.hgt.boys.flat <- extractLMS(fit = f0106r, data=data.t, flatAge=20)
nl4.hgt.boys.flat

# use log age transformation
data.t <- data.frame(data, t.age = log(data$age))
f0106rlog <- gamlss(hgt~cs(t.age,df=10,c.spar=c(-1.5,2.5)),
                sigma.formula=~cs(t.age,df=6,c.spar=c(-1.5,2.5)),
                data=data.t,family=NO,
                control=gamlss.control(n.cyc=1))

nl4.hgt.boys.log <- extractLMS(fit = f0106rlog, data=data.t)
nl4.hgt.boys.log

## End(Not run)

AGD documentation built on May 29, 2024, 3:19 a.m.