help fracpoly, help fracgen dialogs: fracpoly fracgen
also see: fracpoly postestimation
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Title
[R] fracpoly -- Fractional polynomial regression
Syntax
Fractional polynomial regression
fracpoly [, fracpoly_options] : regression_cmd [yvar1 [yvar2]] xvar1
[# [#...]] [xvar2 [# [#...]]] [...] [xvarlist] [if] [in] [
weight] [, regression_cmd_options]
Display table showing the best fractional polynomial model for each
degree
fracpoly , compare
Create variables containing fractional polynomial powers
fracgen varname # [# ...] [if] [in] [, fracgen_options]
fracpoly_options description
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Model
degree(#) degree of fractional polynomial to fit;
default is degree(2)
Model 2
noscaling suppress scaling of first independent
variable
noconstant suppress constant term
powers(numlist) list of fractional polynomial powers from
which models are chosen
center(cent_list) specification of centering for the
independent variables
Reporting
log display iteration log
compare compare models by degree
all include out-of-sample observations in
generated variables
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regression_cmd_options description
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Model 2
regression_cmd_options options appropriate to the regression command
in use
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All weight types supported by regression_cmd are allowed; see weight.
See [R] fracpoly postestimation for features available after estimation.
where
cent_list is a comma-separated list with elements
varlist:{mean|#|no}, except that the first element may optionally be
of the form {mean|#|no} to specify the default for all variables.
regression_cmd may be clogit, glm, intreg, logistic, logit, mlogit,
nbreg, ologit, oprobit, poisson, probit, qreg, regress, rreg, stcox,
streg, or xtgee.
fracgen_options description
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Main
center(no|mean|#) center varname as specified; default is
center(no)
noscaling suppress scaling of varname
restrict([varname] [if]) compute centering and scaling using specified
subsample
replace replace variables if they exist
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Menu
fracpoly
Statistics > Linear models and related > Fractional polynomials >
Fractional polynomial regression
fracgen
Statistics > Linear models and related > Fractional polynomials >
Create fractional polynomial powers
Description
fracpoly fits fractional polynomials (FPs) in xvar1 as part of the
specified regression model. After execution, fracpoly leaves variables
in the dataset named Ixvar__1, Ixvar__2, ..., where xvar represents the
first four letters of the name of xvar1. The new variables contain the
best-fitting FP powers of xvar1.
Covariates other than xvar1, which are optional, are specified in xvar2,
..., and xvarlist. They may be modeled linearly and with specified FP
transformations. Fractional polynomial powers are specified by typing
numbers after the variable's name. A variable name typed without numbers
is entered linearly.
fracgen creates new variables named varname_1, varname_2, ..., containing
FP powers of varname by using the powers (#[# ...]) specified.
See [R] fracpoly postestimation for information on fracplot and fracpred.
See [R] mfp for multivariable FP model fitting.
Options for fracpoly
+-------+
----+ Model +------------------------------------------------------------
degree(#) determines the degree of FP to be fit. The default is
degree(2), i.e., a model with two power terms.
+---------+
----+ Model 2 +----------------------------------------------------------
noscaling suppresses scaling of xvar1 and its powers.
noconstant suppresses the regression constant if this is permitted by
regression_cmd.
powers(numlist) is the set of FP powers from which models are to be
chosen. The default is powers(-2, -1, -.5, 0, .5, 1, 2, 3) (0 means
log).
center(cent_list) defines the centering for the covariates xvar1, xvar2,
..., xvarlist. The default is center(mean). A typical item in
cent_list is varlist:{mean|#|no}. Items are separated by commas.
The first item is special because varlist: is optional, and if
omitted, the default is (re)set to the specified value (mean or # or
no). For example, center(no, age:mean) sets the default to no and
sets the centering for age to mean.
regression_cmd_options are options appropriate to the regression command
in use. For example, for stcox, regression_cmd_options may include
efron or some alternate method for handling tied failures.
+-----------+
----+ Reporting +--------------------------------------------------------
log displays deviances and (for regress) residual standard deviations for
each FP model fit.
compare reports a closed-test comparison between FP models.
all includes out-of-sample observations when generating the best-fitting
FP powers of xvar_1, xvar_2, etc. By default, the generated FP
variables contain missing values outside the estimation sample.
Options for fracgen
+------+
----+ Main +-------------------------------------------------------------
center(no|mean|#) specifies whether varname is to be centered; the
default is center(no).
noscaling suppresses scaling of varname.
restrict([varname] [if]) specifies that centering and scaling be computed
using the subsample identified by varname and if.
The subsample is defined by the observations for which varname!=0
that also meet the if conditions. Typically, varname=1 defines the
subsample and varname=0 indicates observations not belonging to the
subsample. For observations whose subsample status is uncertain,
varname should be set to a missing value; such observations are
dropped from the subsample.
By default, fracgen computes the centering and scaling by using the
sample of observations identified in the [if] [in] options. The
restrict() option identifies a subset of this sample.
replace specifies that any existing variables named varname_1, varname_2,
..., may be replaced.
Examples
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Setup
. webuse igg
Fit a second-degree fractional polynomial regression model
. fracpoly: regress sqrtigg age
Fit a fourth-degree fractional polynomial regression model and compare to
models of lower degrees
. fracpoly, degree(4) compare: regress sqrtigg age
Fit a fractional polynomial regression model using powers -2 and 2
. fracpoly: regress sqrtigg age -2 2
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Setup
. sysuse auto, clear
Create variables containing fractional polynomial powers of -2 and -1 of
mpg without scaling
. fracgen mpg -2 -1 if foreign==1, noscaling replace
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Saved results
In addition to what regression_cmd saves, fracpoly saves the following in
e():
Scalars
e(fp_N) number of nonmissing observations
e(fp_dev) deviance for FP model of degree m
e(fp_df) FP model degrees of freedom
e(fp_d0) deviance for model without xvar_1
e(fp_s0) residual SD for model without xvar_1
e(fp_dlin) deviance for model linear in xvar_1
e(fp_slin) residual SD model linear in xvar_1
e(fp_d1), e(fp_d2), ... deviances for FP models of degree 1,2,...,m
e(fp_s1), e(fp_s2), ... residual SDs for FP models of degree
1,2,...,m
Macros
e(fp_cmd) fracpoly
e(cmdline) command as typed
e(fp_depv) yvar1 (yvar2)
e(fp_rhs) xvar_1
e(fp_base) variables in xvar_2, ..., xvarlist after
centering and FP transformation
e(fp_xp) Ixvar__1, Ixvar__2, etc.
e(fp_fvl) variables in model finally estimated
e(fp_wgt) weight type or ""
e(fp_wexp) weight expression if `e(fp_wgt)' !=""
e(fp_pwrs) powers for FP model of degree m
e(fp_x1), e(fp_x2), ... xvar_1 and variables in model
e(fp_k1), e(fp_k2), ... powers for FP models of degree 1,2,...,m
Residual SDs are stored only when regression_cmd is regress.
Also see
Manual: [R] fracpoly
Help: [R] fracpoly postestimation;
[R] mfp
