dexter (version 0.8.5)

get_responses: Selecting data

Description

Extract data from a dexter database

Usage

get_responses(dataSrc, predicate = NULL, columns = c("person_id",
  "item_id", "item_score"))

Arguments

dataSrc

a dexter project database or data.frame

predicate

an expression to select data on

columns

the columns you wish to select, can include any column in the project, see: get_variables

Value

a data.frame of responses

Details

Many functions in Dexter accept a data source and a predicate. Predicates are extremely flexible but they have a few limitations because they work on the individual response level. It is therefore not possible for example, to remove complete person cases from an analysis based on responses to a single item by using just a predicate expression.

For such cases, Dexter supports selecting the data and manipulating it before passing it back to a Dexter function or possibly doing something else with it. The following example will hopefully clarify this.

Examples

# NOT RUN {
# goal: fit the extended nominal response model using only persons 
# without any missing responses
library(dplyr)

# the following would not work since it will omit only the missing 
# responses, not the persons; which is not what we want in this case
wrong = fit_enorm(db, response != 'NA')

# to select on an aggregate level, we need to gather the data and 
# manipulate it ourselves
data = get_responses(db, 
   columns=c('person_id','item_id','item_score','response')) %>%
   group_by(person_id) %>%
   mutate(any_missing = any(response=='NA')) %>%
   filter(!any_missing)

correct = fit_enorm(data)

# }