# girls: Sempe girls' growth curves data In rrcov3way: Robust Methods for Multiway Data Analysis, Applicable also for Compositional Data

## Description

Thirty girls selected from a French auxiological study (1953-1975) to get insight into the physical growth patterns of children from ages four to fifteen, Sempe (1987). They were measured yearly between the ages 4 and 15 on the following eight variables:

1. weight = Weight

2. length = Length

3. crump = Crown-rump length

4. head = Head circumference

5. chest = Chest circumference

6. arm = Arm

7. calf = Calf

8. pelvis = Pelvis

The data set is three way data array of size 30 (girls) x 8 (variables) x 12 (years).

## Usage

 `1` ```data("girls") ```

## Format

The format is a three way array with the following dimensions: The first dimension refers to 30 girls. The second dimension refers to the eight variables measured on the girls. The third dimension refers to the years – 4 to 15.

## Details

The data are generally preprocessed as standard multiway profile data. For details see Kroonenberg (2008), Chapters 6 and 15.

## Source

The data sets are available from Pieter Kroonenberg's web site at: http://www.leidenuniv.nl/fsw/three-mode/data/girlsgrowthcurvesinfo.htm

## References

Sempe, M. (1987). Multivariate and longitudinal data on growing children: Presentation of the French auxiological survey. In J.Janssen et al. Data analysis. The Ins and Outs of solving real problems (pp. 3-6). New York: Plenum Press.

Kroonenberg (2008). Applied multiway data analysis. Wiley series in probability and statistics. Hoboken NJ, Wiley.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28``` ```data(girls) str(girls) ## Center the data in mode A and find the "average girl" center.girls <- do3Scale(girls, center=TRUE, only.data=FALSE) X <- center.girls\$x center <- center.girls\$center average.girl <- as.data.frame(matrix(center, ncol=8, byrow=TRUE)) dimnames(average.girl) <- list(dimnames(X)[[3]], dimnames(X)[[2]]) ## Divide these variables by 10 to reduce their range average.girl\$weight <- average.girl\$weight/10 average.girl\$length <- average.girl\$length/10 average.girl\$crrump <- average.girl\$crrump/10 average.girl p <- ncol(average.girl) plot(rownames(average.girl), average.girl[,1], ylim=c(min(average.girl), max(average.girl)), type="n", xlab="Age", ylab="") for(i in 1: p) { lines(rownames(average.girl), average.girl[,i], lty=i, col=i) points(rownames(average.girl), average.girl[,i], pch=i, col=i) } legend <- colnames(average.girl) legend[1] <- paste0(legend[1], "*") legend[2] <- paste0(legend[3], "*") legend[3] <- paste0(legend[4], "*") legend("topleft", legend=legend, col=1:p, lty=1:p, pch=1:p) ```

rrcov3way documentation built on June 23, 2017, 4:45 a.m.