interactionRCS (version 0.1.1)

rcsLIN: Restricted cubic spline interaction linear estimates for more than 3 knots

Description

Generate estimates in a linear model for a 1 unit increase in a variable at specified points of another interacting variable splined with rcs(df >= 3)

Usage

rcsLIN(
  var2values,
  model,
  data = NULL,
  var1,
  var2,
  ci = TRUE,
  conf = 0.95,
  ci.method = "delta",
  ci.boot.method = "perc",
  R = 100,
  parallel = "multicore",
  ...
)

Value

if ci = FALSE, a dataframe with initial values and linear estimates , if ci = TRUE a dataframe with 5 columns, initial values, linear estimates, lower CI, upper CI and SE

Arguments

var2values

numeric vector of var2 points to estimate

model

model of class rms::Glm or stats::glm family gaussian. If data is NULL, the function expects to find the data in model$x.

data

data used in the model. If absent, we will attempt to recover the data from the model. Only used for bootstrap

var1

variable that increases by 1 unit from 0

var2

variable to spline. var2values belong to var2

ci

calculate 95% CI?

conf

confidence level. Default 0.95

ci.method

confidence interval method. "delta" performs delta method. "bootstrap" performs bootstrapped CI (slower)

ci.boot.method

one of the available bootstrap CI methods from boot.ci. Default percentile

R

number of bootstrap samples if ci.method = "bootstrap". Default 100

parallel

can take values "no", "multicore", "snow" if ci.method = "bootstrap". Default multicore

...

other parameters for boot

Examples

library(rms)
library(mlbench)
data(PimaIndiansDiabetes)
# Recode diabetes as 0/1
PimaIndiansDiabetes$diabetes <- ifelse(PimaIndiansDiabetes$diabetes=="pos" , 1 , 0)
myformula <- glucose ~ mass + diabetes * rcs(age, 4)
model <- glm(myformula , data = PimaIndiansDiabetes , family="gaussian")
# Show the effect on glucose of being diabetic at age 20 to 80
rcsLIN( var2values = 20:80
       , model = model , data = PimaIndiansDiabetes , var1 ="diabetes", var2="age"
       , ci=TRUE , conf = 0.95 , ci.method = "delta")