Function that transforms functional models from linear or additive functional cox models into afcmSurface
or lfcmSurface
objects to be plotted.
Usage
extract_surface(
mxFDAobject,
metric,
model = NULL,
r = "r",
value = "fundiff",
grid_length = 100,
analysis_vars,
p = 0.05,
filter_cols = NULL
)
Arguments
- mxFDAobject
object of class
mxFDA
with modelmodel
calculated wihtin- metric
spatial summary function to extract surface for
- model
character string for the name of the model for
metric
data- r
Character string, the name of the variable that identifies the function domain (usually a radius for spatial summary functions). Default is "r".
- value
Character string, the name of the variable that identifies the spatial summary function values. Default is "fundiff".
- grid_length
Length of grid on which to evaluate coefficient functions.
- analysis_vars
Other variables used in modeling FCM fit.
- p
numeric p-value used for predicting significant AFCM surface
- filter_cols
a named vector of factors to filter summary functions to in
c(Derived_Column = "Level_to_Filter")
format
Value
a 4 element list of either class lfcmSurface
or afcmSurface
depending on the class of model
- Surface
data.frame
for term predictions for the surface of the metric * radius area- Prediction
data.frame
for standard error of the terms for the above surface. AFCM models use thep
to set the upper and lower standard errors of \(\beta_1\)- Metric
character of the spatial summary function used; helps keep track if running many models
- P-value
a numeric value of the input p-value
Examples
#load ovarian mxFDA object
data('ovarian_FDA')
#run the lfcm model
ovarian_FDA = run_fcm(ovarian_FDA, model_name = "fit_lfcm",
formula = survival_time ~ age, event = "event",
metric = "uni g", r = "r", value = "fundiff",
analysis_vars = c("age", "survival_time"),
afcm = FALSE)
#extract surface
model_surface = extract_surface(ovarian_FDA, metric = 'uni g',
model = 'fit_lfcm',
analysis_vars = 'age') #variables in model