rate_plan: Create a linked data plan for multi-faceted Rasch measurement...
In gtlaflair/rrasch: Rrasch: R Functions for Planning Rasch Analysis with Facets.

Description Usage Arguments Value Examples

View source: R/rate_plan.R

Create a linked data plan for multi-faceted Rasch measurement using Facets.

1 2	rate_plan(responses, tasks, raters, ratings = NULL, benchmarks = NULL, write_tables = FALSE)

`responses`	The number of responses that will be scored. This can be a single integer or a vector of response IDs.
`tasks`	The number of unique tasks. This can be single integer or a vector of task IDs.
`raters`	The number of raters. This can be a single integer or a vector of rater IDs.
`ratings`	The number of times each response will be scored. Default is 2. This should be an integer.
`benchmarks`	Requires a vector of response IDs. This will use the response IDs to create a common set of linking responses for each rater in addition to the indirect links. If NULL, the link is made only through indirect connections,
`write_tables`	TRUE or FALSE. Defaults to FALSE. If TRUE, the function will write three tables to the working directory: rater_view.rds, link_test.csv, and facets_data.xlsx

tables contains two tables.The rater_view table is a dataframe that contains the rater IDs and counts for how many responses the raters will score. In addition, it contains up to two listcolumns: one for the responses that the raters will be scoring and one with the tasks that the raters will be scoring

Unknown response and task IDs

ex_1 <- rate_plan(responses = 1000, tasks = 3, raters = 2, ratings = 2)

Known response and task IDs

resp_ids <- sample(3000:8000, size = 1500, replace = FALSE)
rate_ids <- c('R1', 'R2', 'R3', 'R4', 'R5', 'R6', 'R7', 'R8', 'R9')
task_ids <- c('T1', 'T2', 'T3', 'T4')
benc_ids <- resp_ids[1:10]

ex_2 <- rate_plan(responses = resp_ids, tasks = task_ids, raters = rate_ids, ratings = 3)

ex_3 <- rate_plan(responses = resp_ids, tasks = task_ids, raters = rate_ids, ratings = 3, benchmarks = benc_ids)