gen_z_composite: gen_z_composite

In tessaleejohnson/corclus: Simulate Data from the Correlated Cluster Multiple Membership Model

gen_z_composite

Description

This function takes a matrix of weights .sch_weight and a matrix of predictor values .sch_predictor and constructs the weighted sum as diag(.sch_weight \%*\% t(.sch_predictor)).

Usage

gen_z_composite(.dat, .sch_weight, .sch_predictor)

Arguments

.sch_weight

Numeric matrix with dimensions n x h (where n is the number of persons and h is the maximum number of schools attended by any person in the dataset). Rows should sum to 1 (that is, for each student, the weights assigned to their schools attended should sum to 1). For a school a student did not attend, the weight should be 0 (that is, if the maximum number of schools attended was 2 and person A only attended 1 school, then the weight for their "second school" should be 0, while the weight for their "first school" should be 1). To simulate the data, all students were initially assigned a mobility profile (meaning that all students were assigned h schools to attend), and then only a certain proportion of students were coded as mobile. For the students who were coded as mobile, their .sch_weight matrix row should give equal weight to all schools attended. For students who were coded as non-mobile, their first school was given a weight of 1 and all other schools were given weights of 0.

.sch_predictor

Numeric matrix or dataframe. Contains the values of the school-level predictor, z, generated in gen_u_mmrem.

Value

This function returns a numeric vector of length equal to NROW(.sch_weight) (or, equivalently, NROW(.sch_predictor)). These values are the weighted sum of the predictors constructed for the two schools assigned to all students. For non-mobile students, the z_composite value should be equal to the predictor z from their first school attended.

Examples

## Not run: 

sch_inf <-
  gen_u_mmrem(
    .n_sch = 5,
    .clust_cov = c(.8, .1)
  ) %>%
  expand_sch(., .n_sch = 5, .n_stu = 5) %>%
  assign_mobility(., .n_sch = 5) %>%
  dplyr::mutate(
    .data = .,
    z_composite = gen_z_composite(
      dplyr::select(., sch_wt_1, sch_wt_2),
      dplyr::select(., z_predictor_1, z_predictor_2)
    )
  )


## End(Not run)

tessaleejohnson/corclus documentation built on Oct. 11, 2022, 3:46 a.m.