This repository refers to the paper Kim D., et al.(2020); Inferring Bivariate Association from Respondent-Driven Sampling Data. In this paper, we proposed a method to semi-parametrically estimate the null distributions of standard test statistics in the presence of sampling dependence, allowing for more valid statistical testing for dependence between pairs of variables within the sample.
data contains simulated network data for Section 4.3.3.
R_functions contains all of the R code for all simulations in this paper.
SPRTBA_function.R is a main function for SPRTBA.
Generate.data.1stMC.function.R contains a function for generating data based on 1st order Markov dependence, then code to do a SPRTBA test. (This code is for Sections 4.3.1 and 4.3.2)
simulation.study.1stMC.noassociation.R code for the simulation study for Section 4.3.1 and 4.3.2.
simulation.study.1stMC.association.R code for the simulation study for Section 4.3.3.
latent_space_ftn.R R functions for generating latent space model data and sampling using Respondent Driven sampling, then doing SPRTBA.
simulation_latent_space_dep_unif01.R obtaining simulation results.