R: Class "bounded-continuous"

bounded-continuous-class {mi} | R Documentation

## Class "bounded-continuous"

### Description

The bounded-continuous class inherits from the `continuous-class` and is intended for variables whose observations fall within open intervals that have known boundaries. Although proportions satisfy this definition, the `proportion-class` should be used in that case. At the moment, a bounded continuous variable is modeled as if it were simply a continuous variable, but its `mi-methods` impute the missing values from a truncated normal distribution using the `rtruncnorm` function in the truncnorm package. Note that the default transformation is the identity so if another transformation is used, the bounds must be specified on the transformed data. Aside from these facts, the rest of the documentation here is primarily directed toward developers.

### Objects from the Classes

Objects can be created that are of bounded-continuous class via the the `missing_variable` generic function by specifying `type = "bounded-continuous"` as well as `lower` and / or `upper`

### Slots

The bounded-continuous class inherits from the continuous class and is intended for variables that are supported on a known interval. Its default transformation function is the identity transformation and its `imputation_method` must be `"ppd"`. It has two additional slots:

upper

  a numeric vector whose length is either one or the value of the `n_total` slot giving the upper bound for every observation; `NA`s are not allowed

lower

  a numeric vector whose length is either one or the value of the `n_total` slot giving the lower bound for every observation; `NA`s are not allowed

### Author(s)

Ben Goodrich and Jonathan Kropko, for this version, based on earlier versions written by Yu-Sung Su, Masanao Yajima, Maria Grazia Pittau, Jennifer Hill, and Andrew Gelman.

### See Also

`missing_variable`, `continuous-class`, `positive-continuous-class`, `proportion-class`

### Examples

    # STEP 0: GET DATA
    data(CHAIN, package = "mi")

    # STEP 0.5 CREATE A missing_variable (you never need to actually do this)
    lo_bound <- 0
    hi_bound <- rep(Inf, nrow(CHAIN))
    hi_bound[CHAIN$log_virus == 0] <- 6
    log_virus <- missing_variable(ifelse(CHAIN$log_virus == 0, NA, CHAIN$log_virus),
                                  type = "bounded-continuous", lower = lo_bound, upper = hi_bound)

    show(log_virus)

[Package mi version 1.0 Index]