show_dependencies: Show Associations of Partitioning

In ZytoHMGU/hetset: Identification of Heterogeneous Subsets in Data

Description

A set of categorical variables from the samples of a hetset object is tested for association with the subpopulations found in a scan_hetset run by Fisher's test for independence.

Usage

show_dependencies(H, dep_list, S_list, type = "print")

Arguments

H	hetset object with H$prt labels and supplemental information in H$[dep_list]
dep_list	vector of variable names, that are used for further splittings of the samples
S_list	list of thresholds or reference values for the variables in dep_list
type	"print" (default) the test results to console or add to current "plot"

Details

Odds Ratios and corresponding confidence intervals for the association of the partitioning with sample data are added to the plot produced by plot_hetset

Note

If scan_hetset was initiated by a given classification (e.g. sex), the test must not be executed for the partitioning found by the mixture model and the initial classification information. Since this would represent some kind of a tautology.

Author(s)

Daniel Samaga

Examples

n_A <- 100
n_B <- 50
A <- matrix(data = rnorm(n = n_A*15,mean = 1,sd = 1),ncol = n_A)
B <- matrix(data = rnorm(n = n_B*15,mean = 3,sd = 2),ncol = n_B)
Hds <- hetset(D = cbind(A,B))
Hds$"group" <- c(rep("A",n_A),rep("B",n_B))
Hds$"score" <- rnorm(ncol(Hds))
rm(A,B,n_A,n_B)
Hds <- scan_hetset(H = Hds,level = "univariate",min_size = 2,
    max_size = 3,rel_imp = 0,em_steps = 5)
plot_hetset(Hds)
show_dependencies(H = Hds,dep_list = c("group","score"),S_list = list("A",0),type = "plot")

ZytoHMGU/hetset documentation built on June 6, 2019, 2:16 p.m.