compute_marg_PR_nested_reg_array function

compute positive rates for nested model with subclass mixing weights that are the same across Jcause classes for each person (people may have different weights.)

This is an array-version of compute_marg_PR_nested_reg . This is used in plot_etiology_regression

compute_marg_PR_nested_reg_array(
  ThetaBS_array,
  PsiBS_array,
  pEti_mat_array,
  subwt_mat_array,
  case,
  template
)

Arguments

• ThetaBS_array: An array of: True positive rates for JBrS measures (rows) among K subclasses (columns)
• PsiBS_array: An array of: False positive rates; dimension same as above
• pEti_mat_array: An array of: a matrix of etiology pies for N subjects (rows) and Jcause causes (columns) rows sum to ones.
• subwt_mat_array: An array of: a matrix of subclass weights for cases and controls. N by K. Rows sum to ones.
• case: a N-vector of 1s (cases) and 0s (controls)
• template: a binary matrix with Jcause+1 rows (Jcause classes of cases and 1 class of controls) and JBrS columns for the Bronze-standard measurement (say, pick one type/slice). The ones in each row indicate the measurements that will show up more frequently in cases given the cause.

Returns

An array of: a matrix of values between 0 and 1 (need not to have row sums of ones); of dimension (number of subjects, dimension of the bronze-standard measurement slice).