postpi: postpi function provides the corrected inference result table...

In SiruoWang/IAP: What the Package Does (One Line, Title Case)

Description

This function is required to take in the relationship model from 'postpi_relate()', a validation set, and the inference formula. Through a bootstrap approach, the function quantifies biases using the relationship model and then corrects the inference results in the validation set based on the input inference formula. The default number of bootstrapping is 100 and the seed is 1234. Both parameters can be defined by users.

Usage

postpi(
  valid_dat,
  rel_model,
  inf_formula,
  method = "par",
  bs = 100,
  seed = NULL
)

Arguments

valid_dat	validation set that contains only the predicted outcomes and covariates of interest
rel_model	model object created by 'postpi_relate()'
inf_formula	inference formula for fitting predicted outcomes ~ covariates, eg. yp ~ x1
method	parametric or non-parametric method to estimate standard error of estimates. Method = "par" or "non-par". The default value is "par", parametric method.
bs	number of bootstrap times. The default value is 100 times.
seed	seed number. The default value is 1234

Value

tidytable a tidy table for inference results. It contains conlumns: term, estimate, std.error, statistic, p.value

Examples

data(RINdata,package="postpi")

testing    <- RINdata[1:2000,]
validation <- RINdata[2001:nrow(RINdata),]

relation_dat   <- data.frame(actual = testing$actual, predictions = testing$predictions)
relation_model <- postpi_relate(relation_dat,actual)

inf_par    <- postpi(validation, relation_model, predictions ~ region_1)
inf_nonpar <- postpi(validation, relation_model, predictions ~ region_1, method = "non-par")

SiruoWang/IAP documentation built on Sept. 20, 2020, 4 a.m.