Description Usage Arguments Details Value
Generate simulation datasets for change point Monte Carlo studies.
1 2 3 4 5 6 7 8 9 10 11 12  sim.chngpt (
mean.model=c("thresholded","thresholdedItxn","quadratic","quadratic2b",
"cubic2b","exp","flatHyperbolic"),
threshold.type=c("NA","step","hinge","segmented","segmented2","stegmented"),
b.transition=Inf,
family=c("binomial","gaussian"),
x.distr=c("norm","norm3","norm6","imb","lin","mix","gam","zbinary","gam1","gam2"),
e.=NULL, mu.x=4.7, sd.x=NULL, sd=0.3,
alpha=NULL, alpha.candidate=NULL, coef.z=log(1.4), beta=NULL, beta.itxn=NULL,
n, seed,
weighted=FALSE, # sampling weights
verbose=FALSE)

threshold.type 
string. Types of threshold effect to simulate, only applicable when label does not start with sigmoid. 
family 
string. Glm family. 
n 

seed 

weighted 

beta 

coef.z 
numeric. Coefficient for z. 
beta.itxn 
numeric. Coefficient for z. 
alpha 
numeric, intercept. 
mu.x 
numeric 
sd.x 
numeric 
mean.model 
numeric 
x.distr 
string. Possible values: norm (normal distribution), gam (gamma distribution). gam1 is a hack to allow e. be different 
e. 

verbose 
Boolean 
b.transition 

sd 

alpha.candidate 
candidate values of alpha, used in code to determine alpha values 
mean.model, threshold.type and b.transition all affect mean models.
A data frame with following columns:
y 
0/1 outcome 
x 
observed covariate that we are interested in 
x.star 
unobserved covariate that underlies x 
z 
additional covariate 
In addition, columns starting with 'w' are covariates that we also adjust in the model; columns starting with 'x' are covariates derived from x.
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