xmfp -- Multivariable fractional polynomial models with extensions


xmfp [, options] : regression_cmd [yvar1 [yvar2]] xvarlist [if] [in] [weight] [, regression_cmd_options]

options Description ------------------------------------------------------------------------- Model 2 sequential use the Royston and Altman model-selection algorithm; default uses closed-test procedure cycles(#) maximum number of iteration cycles; default is cycles(5) dfdefault(#) default maximum degrees of freedom; default is dfdefault(4) center(cent_list) specification of centering for the independent variables alpha(alpha_list) p-values for testing between FP models; default is alpha(0.05) df(df_list) degrees of freedom for each predictor powers(numlist) list of FP powers to use; default is powers(-2 -1(.5)1 2 3) linadj(varlist) list of variables to be included as untransformed linear terms in all MFP models

Adv. model xorder(+|-|n) order of entry into model-selection algorithm; default is xorder(+) select(select_list) nominal p-values for selection on each predictor xpowers(xp_list) FP powers for each predictor zero(varlist) treat nonpositive values of specified predictors as zero when FP is transformed catzero(varlist) add indicator variable for specified predictors all include out-of-sample observations in generated variables

Reporting level(#) set confidence level; default is level(95) display_options control column formats and line width -------------------------------------------------------------------------

regression_cmd_options Description ------------------------------------------------------------------------- Adv. model regression_cmd_options options appropriate to the regression command in use -------------------------------------------------------------------------

All weight types supported by regression_cmd are allowed; see weight. See [R] mfp postestimation for features available after estimation. fracgen may be used to create new variables containing fractional polynomial powers. See [R] fracpoly.


regression_cmd may be clogit, glm, intreg, logistic, logit, mlogit, nbreg, ologit, oprobit, poisson, probit, qreg, regress, rreg, stcox, stcrreg, streg, or xtgee.

yvar1 is not allowed for streg, stcrreg, and stcox. For these commands, you must first stset your data.

yvar1 and yvar2 must both be specified when regression_cmd is intreg.

xvarlist has elements of type varlist and/or (varlist); for example,

x1 x2 (x3 x4 x5)

Elements enclosed in parentheses are tested jointly for inclusion in the model and are not eligible for fractional polynomial transformation.


xmfp selects the multivariable fractional polynomial (MFP) model that best predicts the outcome variable from the right-hand-side variables in xvarlist.

xmfp provides some extensions to the factory-standard mfp command, namely

1. xmfp supports factor variables 2. xmfp has a linadj(varlist) option to adjust linearly for variables in va > rlist.

Note also that the mfp post-estimation commands fracplot and fracpred are replaced with xfracplot and xfracpred, respectively. The syntax is unchanged, except that xfracplot has an additional option nopts which suppresses plotting of partial residuals.


Patrick Royston MRC Clinical Trials Unit London, UK pr@ctu.mrc.ac.uk

Also see

Manual: [R] fracpoly, [R] mfp

Online: mfp