| dynamicGP {pcatsAPIclientR} | R Documentation |
Performs a data analysis for data with adaptive treatments.
Description
Performs Bayesian's Gaussian process regression or Bayesian additive regression tree for data with adaptive treatment(s).
Usage
dynamicGP(
datafile = NULL,
dataref = NULL,
method = "BART",
stg1.outcome,
stg1.treatment,
stg1.x.explanatory = NULL,
stg1.x.confounding = NULL,
stg1.tr.hte = NULL,
stg1.tr.values = NULL,
stg1.tr.type = "Discrete",
stg1.time,
stg1.time.value = NULL,
stg1.outcome.type = "Continuous",
stg1.outcome.bound_censor = "neither",
stg1.outcome.lb = NULL,
stg1.outcome.ub = NULL,
stg1.outcome.censor.lv = NULL,
stg1.outcome.censor.uv = NULL,
stg1.outcome.censor.yn = NULL,
stg1.outcome.link = "identity",
stg1.c.margin = NULL,
stg2.outcome,
stg2.treatment,
stg2.x.explanatory = NULL,
stg2.x.confounding = NULL,
stg2.tr1.hte = NULL,
stg2.tr2.hte = NULL,
stg2.tr.values = NULL,
stg2.tr.type = "Discrete",
stg2.time,
stg2.time.value = NULL,
stg2.outcome.type = "Continuous",
stg2.outcome.bound_censor = "neither",
stg2.outcome.lb = NULL,
stg2.outcome.ub = NULL,
stg2.outcome.censor.lv = NULL,
stg2.outcome.censor.uv = NULL,
stg2.outcome.censor.yn = NULL,
stg2.outcome.link = "identity",
stg2.c.margin = NULL,
burn.num = 500,
mcmc.num = 500,
x.categorical = NULL,
mi.datafile = NULL,
mi.dataref = NULL,
sheet = NULL,
mi.sheet = NULL,
seed = 5000,
token = NULL,
use.cache = NULL
)
Arguments
datafile |
File to upload (.csv or .xls) |
dataref |
Reference to already uploaded file. |
method |
The method to be used. "GP" for GP method and "BART" for BART method. The default value is "BART". |
stg1.outcome |
The name of the intermediate outcome variable for stage 1. |
stg1.treatment |
The name of the treatment variable for stage 1. |
stg1.x.explanatory |
A vector of the name of the explanatory variables for stage 1. |
stg1.x.confounding |
A vector of the name of the confounding variables for stage 1. |
stg1.tr.hte |
An optional vector specifying categorical variables which may have heterogeneous treatment effect with the treatment variable for stage 1. |
stg1.tr.values |
User-defined values for the calculation of ATE if the treatment variable is continuous for stage 1. |
stg1.tr.type |
The type of treatment at stage 1. "Continuous" for continuous treatment and "Discrete" for categorical treatment. The default value is "Discrete". |
stg1.time |
Time variable. |
stg1.time.value |
Pre-specified time exposure. |
stg1.outcome.type |
Intermediate outcome type ("Continuous" or "Discrete") for stage 1. |
stg1.outcome.bound_censor |
The default value is "neither". "neither" if the intermediate outcome is not bounded or censored. "bounded" if the intermediate outcome is bounded. "censored" if the intermediate outcome is censored. |
stg1.outcome.lb |
Stage 1 lower bound if the intermediate outcome is bounded. |
stg1.outcome.ub |
Stage 1 upper bound if the intermediate outcome is bounded. |
stg1.outcome.censor.lv |
lower variable of censored interval if the intermediate outcome is censored. |
stg1.outcome.censor.uv |
upper variable of censored interval if the intermediate outcome is censored. |
stg1.outcome.censor.yn |
Censoring variable if the intermediate outcome is censored. |
stg1.outcome.link |
function for the intermediate outcome; the default value is “identity”. "identity" if no transformation needed. "log" for log transformation. "logit" for logit transformation. |
stg1.c.margin |
An optional vector of user-defined values of c for PrTE at stage 1. |
stg2.outcome |
The name of the outcome variable for stage 2. |
stg2.treatment |
The name of the treatment variable for stage 2. |
stg2.x.explanatory |
A vector of the name of the explanatory variables for stage 2. |
stg2.x.confounding |
A vector of the name of the confounding variables for stage 2. |
stg2.tr1.hte |
At stage 2, an optional vector specifying categorical variables which may have heterogeneous treatment effect with the stage 1 treatment variable |
stg2.tr2.hte |
At stage 2, an optional vector specifying categorical variables which may have heterogeneous treatment effect with the stage 2 treatment variable |
stg2.tr.values |
User-defined values for the calculation of ATE if the treatment variable is continuous for stage 2. |
stg2.tr.type |
The type of treatment at stage 2. "Continuous" for continuous treatment and "Discrete" for categorical treatment. The default value is "Discrete". |
stg2.time |
Time variable. |
stg2.time.value |
Pre-specified time exposure. |
stg2.outcome.type |
Outcome type ("Continuous" or "Discrete") for stage 2. |
stg2.outcome.bound_censor |
The default value is "neither". "neither" if the intermediate outcome is not bounded or censored. "bounded" if the intermediate outcome is bounded. "censored" if the intermediate outcome is censored. |
stg2.outcome.lb |
Stage 2 lower bound if the outcome is bounded. |
stg2.outcome.ub |
Stage 2 upper bound if the outcome is bounded. |
stg2.outcome.censor.lv |
lower variable of censored interval if the outcome is censored. |
stg2.outcome.censor.uv |
upper variable of censored interval if the outcome is censored. |
stg2.outcome.censor.yn |
Censoring variable if the outcome is censored. |
stg2.outcome.link |
function for the outcome; the default value is “identity”. "identity" if no transformation needed. "log" for log transformation. "logit" for logit transformation. |
stg2.c.margin |
An optional vector of user-defined values of c for PrTE at stage 2. |
burn.num |
numeric; the number of MCMC 'burn-in' samples, i.e. number of MCMC to be discarded. The default value is 500. |
mcmc.num |
numeric; the number of MCMC samples after 'burn-in'. The default value is 500. |
x.categorical |
A vector of the name of categorical variables in data. |
mi.datafile |
File to upload (.csv or .xls) that contains the imputed data in the model. |
mi.dataref |
Reference to already uploaded file that contains the imputed data in the model. |
sheet |
If |
mi.sheet |
If |
seed |
Sets the seed. The default value is 5000. |
token |
Authentication token. |
use.cache |
Use cached results (default True). |
Value
jobid