Export the interview records

Export the interview records (data and dictionary) of interview step(s).

Usage

amber.interview_export(
  amber,
  study = NULL,
  interviewDesign = NULL,
  campaign = NULL,
  from = NULL,
  to = NULL,
  completed = NULL,
  code = NULL,
  identifier = NULL,
  state = NULL,
  participantValid = NULL,
  query = list(),
  skip = 0,
  limit = 100,
  df = TRUE
)

Arguments

amber

An Amber object

study

Study identifier (name or id), optional.

interviewDesign

Interview design identifier (name or id), optional.

campaign

Campaign identifier (name or id), optional.

from

From date (included), optional

to

To date (included), optional

completed

When TRUE export data from completed interviews only (default is NULL)

code

Participant interview code

identifier

Patient/participant study identifier

state

State of the interview: 'initiated', 'in_progress', 'completed'

participantValid

Participant is valid (logical): active and in the valid date range

query

The search query

skip

Number of items to skip

limit

Max number of items

df

Return a data.frame (default is TRUE)

Value

A named list of data.frames, a data dictionary and a data data.frame per form revision (or a named list of raw results when 'df' is FALSE)

See also

Other studies functions: amber.campaign(), amber.campaigns(), amber.case_report_export(), amber.case_report_form(), amber.case_report_forms(), amber.case_reports(), amber.form(), amber.form_revision(), amber.form_revisions(), amber.forms(), amber.interview_design(), amber.interview_designs(), amber.interviews(), amber.interviews_step_actions(), amber.interviews_step_data(), amber.interviews_steps(), amber.participant(), amber.participants(), amber.studies(), amber.study()

Examples

if (FALSE) { # \dontrun{
a <- amber.login("https://amber-demo.obiba.org")

# Extract data from all interviews
amber.interview_export(a)

# Extract data from all completed interviews
amber.interview_export(a, completed = TRUE)

# Extract data from all interviews in a range of time
amber.interview_export(a, from = "2022-01-12 00:00", to = "2022-02-13")

# Extract data from all interviews for a specific participant/patient
# study identifier
amber.interview_export(a, identifier = "1231")

# Extract data from all interviews having their participant study
# identifier matching a regular expression
amber.interview_export(a, query = list(`identifier[$search]` = "^12"))

# Extract data from all interviews having their participant attributes
# matching a value
# (will not work if the data are encrypted in the database)
amber.interview_export(a, query = list(data.country = "fr"))

# Export records collected with a study's interview design
tables <- amber.interview_export(a,
  study = "liftup",
  interviewDesign = "treocapa_lt")

# Result contains both data and dictionary
tables

# Tables are named with the <interview design name>-<form name>-<revision> pattern
names(tables)

# Merge datasets from different versions if relevant
dplyr::bind_rows(lapply(tables, function (t) {
  t$data
}))

amber.logout(a)
} # }