# growthcurve

##### Compare Groups of Growth Curves

Do all pairwise comparisons between groups of growth curves using a permutation test.

- Keywords
- regression

##### Usage

```
compareGrowthCurves(group, y, levels=NULL, nsim=100, fun=meanT, times=NULL,
verbose=TRUE, adjust="holm")
compareTwoGrowthCurves(group, y, nsim=100, fun=meanT)
plotGrowthCurves(group, y, levels=sort(unique(group)), times=NULL, col=NULL,...)
```

##### Arguments

- group
vector or factor indicating group membership. Missing values are allowed in

`compareGrowthCurves`

but not in`compareTwoGrowthCurves`

.- y
matrix of response values with rows for individuals and columns for times. The number of rows must agree with the length of

`group`

. Missing values are allowed.- levels
a character vector containing the identifiers of the groups to be compared. By default all groups with two more more members will be compared.

- nsim
number of permutations to estimated p-values.

- fun
a function defining the statistic used to measure the distance between two groups of growth curves. Defaults to

`meanT`

.- times
a numeric vector containing the column numbers on which the groups should be compared. By default all the columns are used.

- verbose
should progress results be printed?

- adjust
method used to adjust for multiple testing, see

`p.adjust`

.- col
vector of colors corresponding to distinct groups

- ...
other arguments passed to

`plot()`

##### Details

`compareTwoGrowthCurves`

performs a permutation test of the difference between two groups of growth curves.
`compareGrowthCurves`

does all pairwise comparisons between two or more groups of growth curves.
Accurate p-values can be obtained by setting `nsim`

to some large value, `nsim=10000`

say.

##### Value

`compareTwoGrowthCurves`

returns a list with two components, `stat`

and `p.value`

, containing the observed statistics and the estimated p-value. `compareGrowthCurves`

returns a data frame with components

name of first group in a comparison

name of second group in a comparison

observed value of the statistic

estimated p-value

p-value adjusted for multiple testing

##### References

Elso, C. M., Roberts, L. J., Smyth, G. K., Thomson, R. J., Baldwin, T. M.,
Foote, S. J., and Handman, E. (2004). Leishmaniasis host response loci
(lmr13) modify disease severity through a Th1/Th2-independent pathway.
*Genes and Immunity* 5, 93-100.

Baldwin, T., Sakthianandeswaren, A., Curtis, J., Kumar, B., Smyth, G. K., Foote, S., and Handman, E. (2007).
Wound healing response is a major contributor to the severity of cutaneous leishmaniasis in the ear model of infection.
*Parasite Immunology* 29, 501-513.

##### See Also

##### Examples

```
# NOT RUN {
# A example with only one time
data(PlantGrowth)
compareGrowthCurves(PlantGrowth$group,as.matrix(PlantGrowth$weight))
# Can make p-values more accurate by nsim=10000
# }
```

*Documentation reproduced from package statmod, version 1.4.32, License: GPL-2 | GPL-3*