Predict SITAR model
Predict method for sitar objects, based on predict.lme.
## S3 method for class 'sitar' predict( object, newdata = getData(object), level = 1L, ..., deriv = 0L, abc = NULL, xfun = function(x) x, yfun = function(y) y )
object |
an object inheriting from class |
newdata |
an optional data frame to be used for obtaining the
predictions, defaulting to the data used to fit |
level |
an optional integer vector giving the level(s) of grouping to be used
in obtaining the predictions, level 0 corresponding to the population
predictions. Defaults to level 1, and |
... |
other optional arguments: |
deriv |
an optional integer specifying predictions corresponding to
either the fitted curve or its derivative. |
abc |
an optional named vector containing values of a subset of
|
xfun |
an optional function to apply to |
yfun |
an optional function to apply to |
When deriv = 1 the returned velocity is in units of yfun(y)
per xfun(x). So if x and/or y are transformed, velocity
in units of y per x can be obtained by specifying xfun
and/or yfun to back-transform them appropriately.
A vector of the predictions, or a list of vectors if asList =
TRUE and level == 1, or a data frame if length(level) > 1.
Tim Cole tim.cole@ucl.ac.uk
ifun for a way to generate the functions xfun
and yfun automatically from the sitar model call.
data(heights) ## fit model m1 <- sitar(x=age, y=height, id=id, data=heights, df=5) ## predictions at level 0 predict(m1, newdata=data.frame(age=9:16), level=0) ## predictions at level 1 for subject 5 predict(m1, newdata=data.frame(age=9:16, id=5), level=1) ## velocity predictions for subjects with early and late puberty vel1 <- predict(m1, deriv=1, abc=c(b=-1)) mplot(age, vel1, id, heights, col=id) vel1 <- predict(m1, deriv=1, abc=c(b=1)) mplot(age, vel1, id, heights, col=id, add=TRUE)
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