1d:T7a9,# Adjust x and y variables for SITAR random effects `xyadj` Adjusts `x` and `y` and optionally `v` values for subject-specific random effects from a SITAR model. ```r xyadj(object, x, y = 0, v = 0, id, abc = NULL, tomean = TRUE) ``` ## Arguments - `object`: a SITAR model. - `x`: a vector of x coordinates. If missing, `x` and `y` and `id` are obtained from `object`. - `y`: a vector of y coordinates (default 0). - `v`: a vector of velocity coordinates (default 0). - `id`: a factor denoting the subject levels corresponding to `x` and `y` and `v`. - `abc`: a data frame containing random effects for a, b, c and d (default `ranef(object)[id, ]`). - `tomean`: a logical defining the direction of adjustment. TRUE (default) indicates that individual curves are translated and rotated to match the mean curve, while FALSE indicates the reverse, the mean curve being translated and rotated to match individual curves. ## Returns The list of adjusted values: - **x**: numeric vector. - **y**: numeric vector the same length as x, or NULL. - **v**: numeric vector the same length as x, or NULL. ## Details When `tomean = TRUE` the x and y and v values are adjusted to $$ (x - xoffset - b - b) * exp(c) + xoffset + b $$ $$ y - a - d * x $$ $$ (v - d) / exp(c) $$ When `tomean = FALSE` they are adjusted to $$ (x - xoffset - b) / exp(c) + xoffset + b + b $$ $$ y + a + d * x $$ $$ v * exp(c) + d $$ In each case missing values of the fixed or random effects are set to zero. ## Examples ```r data(heights) ## fit sitar model for height m1 <- sitar(x = age, y = height, id = id, data = heights, df = 5) ## plot unadjusted data as growth curves plot(m1, opt='u') ## overplot with adjusted data as points with(heights, points(xyadj(m1), col='red', pch = 19)) ``` ## Author(s) Tim Cole tim.cole@ucl.ac.uk

xyadj function