Comp.Mix {CompMix}

A comprehensive toolkit for environmental mixtures analysis

Description

A comprehensive toolkit for environmental mixtures analysis

Usage

Comp.Mix(
  y,
  x,
  z = NULL,
  y.type,
  test.pct = 0.5,
  var.select = NULL,
  interaction = NULL,
  interaction.exp.cov = NULL,
  covariates.forcein = NULL,
  bkmr.pip = 0.5,
  bkmr.iter = 500,
  formula = NULL,
  expnms = NULL,
  seed = 1234,
  verbose = TRUE
)

Arguments

y

A vector of either continuous or binary values to indicate the health outcome

x

A matrix of numeric values to indicate the chemical mixtures

z

A matrix of numeric values to indicate the covariates

y.type

A character value of either "continuous" or "binary"

test.pct

A numeric scalar between 0 and 1 to indicate the proportion allocated as test samples

var.select

A logical value to indicate whether to perform variable selection

interaction

A logical value (TRUE/FALSE) to indicate whether to include pairwise interaction terms between all the chemical mixtures x

interaction.exp.cov

A logical value (TRUE/FALSE) to indicate whether to include pairwise interaction terms between all the chemical mixtures x and covariates z. If interaction.exp.cov=TRUE, interaction=TURE or interaction=FALSE will be ignored

covariates.forcein

A logical value (TRUE/FALSE) to indicate whether to force in any covariates

bkmr.pip

A numeric scalar between 0 and 1 to indicate the cutoff for the posterior inclusion probability in BKMR

bkmr.iter

A positive integer to indicate the number of MCMC iterations for bkmr

formula

the formula for qgcomp and wqs

expnms

a vector of characters for names of exposure variables

seed

an integer value for seed

verbose

a logical value to show information

Value

A list object which may contain up to 8 cases

Case 1

variable selection on main effects for exposures and confounders

Each case may contain some of the following elements

betaest

a numeric vector of coeffcients for the exposures

z_betaest

a numeric vector of coeffcients for the covariates

sse

A positive scalar to indicate sum of squares error

corr

A numeric scalar between -1 and 1 to indicate correlation coefficient

Author(s)

Wei Hao <[e-mail]>

Examples

dat <- lmi_simul_dat(n=1000,p=20,q=5,
block_idx=c(1,1,2,2,3,1,1,1,1,1,2,2,2,2,3,3,3,3,3,3),
within_rho=0.6,btw_rho=0.1,R2=0.2,
effect_size=1,effect_size_i=1,
cancel_effect = FALSE)
#Example 1: The users would like to perform variable selections
#on main effects of exposures and covariates, and outcome, exposures and
#covariates are entered. For any individual interactions that the users would
#like to include in the models, they can add those into the covariate z.
res_ex1 <- Comp.Mix(y.type="continuous",y=dat$y, x=dat$x, z=dat$z, test.pct=0.5,
var.select = TRUE, interaction = FALSE, interaction.exp.cov = FALSE,
covariates.forcein = FALSE,
bkmr.pip=0.5, seed=2023)