generates the different simulation scenarios. This function is
not intended to be called directly by users. See gendata
gendataPaper(n, p, corr = 0, E = truncnorm::rtruncnorm(n, a = -1, b =
1), betaE = 2, SNR = 2, hierarchy = c("strong", "weak", "none"),
nonlinear = TRUE, interactions = TRUE, causal, not_causal)number of observations
number of main effect variables (X)
correlation between predictors
simulated environment vector of length n. Can be continuous
or integer valued. Factors must be converted to numeric. Default:
truncnorm::rtruncnorm(n, a = -1, b = 1)
exposure effect size
signal to noise ratio
type of hierarchy. Can be one of c("strong", "weak",
"none"). Default: "strong"
simulate non-linear terms (logical). Default: TRUE
simulate interaction (logical). Default: TRUE
character vector of causal variable names
character vector of noise variables
A list with the following elements:
matrix of
dimension nxp of simulated main effects
simulated response
vector of length n
simulated exposure vector of length
n
linear predictor vector of length n
the function f1 evaluated at x_1 (f1(X1))
the function f1 evaluated at x_1 (f1(X1))
the function f1 evaluated at x_1 (f1(X1))
the function f1 evaluated at x_1 (f1(X1))
the value for \(\beta_E\)
the function
f1
the function f2
the function
f3
the function f4
an n length
vector of the first predictor
an n length vector of the
second predictor
an n length vector of the third
predictor
an n length vector of the fourth predictor
a character representing the simulation scenario identifier as described in Bhatnagar et al. (2018+)
character vector of causal variable names
character vector of noise variables
Requires installation of truncnorm package. Not meant to be
called directly by user. Use gendata.