Package 'acro'

Title: A Tool for Semi-Automating the Statistical Disclosure Control of Research Outputs
Description: A Tool for Semi-Automating the Statistical Disclosure Control of Research Outputs.
Authors: Jim Smith [cre, ctb] (ORCID: <https://orcid.org/0000-0001-7908-1859>), Maha Albashir [aut, ctb], Richard John Preen [aut, ctb] (ORCID: <https://orcid.org/0000-0003-3351-8132>)
Maintainer: Jim Smith <[email protected]>
License: MIT + file LICENSE
Version: 0.1.7
Built: 2026-05-20 14:05:46 UTC
Source: https://github.com/ai-sdc/acro-r

Help Index

Add comments to outputs

Description

Add comments to outputs

Usage

acro_add_comments(name, comment)

Arguments

name

The name of the output.
comment

The comment.

Value

No return value, called for side effects

Adds an exception request to an output.

Description

Adds an exception request to an output.

Usage

acro_add_exception(name, reason)

Arguments

name

The name of the output.
reason

The comment.

Value

No return value, called for side effects

Compute a simple cross tabulation of two (or more) factors.

Description

Compute a simple cross tabulation of two (or more) factors.

Usage

acro_crosstab(index, columns, values = NULL, aggfunc = NULL)

Arguments

index

Values to group by in the rows.
columns

Values to group by in the columns.
values

Array of values to aggregate according to the factors. Requires aggfunc be specified.
aggfunc

If specified, requires values be specified as well.

Value

Cross tabulation of the data

Adds an unsupported output to the results dictionary

Description

Adds an unsupported output to the results dictionary

Usage

acro_custom_output(filename, comment = NULL)

Arguments

filename

The name of the file that will be added to the list of the outputs.
comment

An optional comment.

Value

No return value, called for side effects

Turns suppression off during a session

Description

Turns suppression off during a session

Usage

acro_disable_suppression()

Value

No return value, called for side effects

Turns suppression on during a session

Description

Turns suppression on during a session

Usage

acro_enable_suppression()

Value

No return value, called for side effects

Creates a results file for checking.

Description

Creates a results file for checking.

Usage

acro_finalise(path, ext)

Arguments

path

Name of a folder to save outputs.
ext

Extension of the results file. Valid extensions are json or xlsx.

Value

No return value, called for side effects

Fits Logit or Probit model.

Description

Fits Logit or Probit model.

Usage

acro_glm(formula, data, family)

Arguments

formula

The formula specifying the model.
data

The data for the model.
family

Decide whether to fit a logit or probit model.

Value

Regression Results Wrapper

Histogram

Description

Histogram

Usage

acro_hist(
  data,
  column,
  breaks = 10,
  freq = TRUE,
  col = NULL,
  filename = "histogram.png"
)

Arguments

data

The object holding the data.
column

The column that will be used to plot the histogram.
breaks

Number of histogram bins to be used.
freq

If False, the result will contain the number of samples in each bin. If True, the result is the value of the probability density function at the bin.
col

The color of the plot.
filename

The name of the file where the plot will be saved.

Value

The histogram.

Initialise an ACRO object

Description

Initialise an ACRO object

Usage

acro_init(
  config = "default",
  suppress = FALSE,
  envname = acro_venv,
  use_conda = NULL
)

Arguments

config

Name of a yaml configuration file with safe parameters.
suppress

Whether to automatically apply suppression.
envname

Name of the Python environment to use.
use_conda

Whether to use a Conda environment. If NULL, looks for environment variable ACRO_USE_CONDA, defaults to FALSE if unset.

Value

Invisibly returns the ACRO object, which is used internally.

Fits Ordinary Least Squares Regression

Description

Fits Ordinary Least Squares Regression

Usage

acro_lm(formula, data)

Arguments

formula

The formula specifying the model.
data

The data for the model.

Value

Regression Results Wrapper.

Pivot table

Description

Pivot table

Usage

acro_pivot_table(
  data,
  values = NULL,
  index = NULL,
  columns = NULL,
  aggfunc = "mean"
)

Arguments

data

The data to operate on.
values

Column to aggregate, optional.
index

If an array is passed, it must be the same length as the data. The list can contain any of the other types (except list). Keys to group by on the pivot table index. If an array is passed, it is being used as the same manner as column values.
columns

If an array is passed, it must be the same length as the data. The list can contain any of the other types (except list). Keys to group by on the pivot table column. If an array is passed, it is being used as the same manner as column values.
aggfunc

If list of strings passed, the resulting pivot table will have hierarchical columns whose top level are the function names

Value

Cross tabulation of the data.

Prints the current results dictionary.

Description

Prints the current results dictionary.

Usage

acro_print_outputs()

Value

No return value, called for side effects

Remove outputs

Description

Remove outputs

Usage

acro_remove_output(name)

Arguments

name

Key specifying which output to remove, e.g., 'output_0'.

Value

No return value, called for side effects

Rename outputs

Description

Rename outputs

Usage

acro_rename_output(old, new)

Arguments

old

The old name of the output.
new

The new name of the output.

Value

No return value, called for side effects

Survival analysis

Description

Survival analysis

Usage

acro_surv_func(time, status, output, filename = "kaplan-meier.png")

Arguments

time

An array of times (censoring times or event times).
status

Status at the event time.
output

A string determine the type of output. Available options are table or plot.
filename

The name of the file where the plot will be saved.

Value

The survival table or plot.

Compute a simple cross tabulation of two (or more) factors.

Description

Compute a simple cross tabulation of two (or more) factors.

Usage

acro_table(index, columns, dnn = NULL, deparse.level = 0, ...)

Arguments

index

Values to group by in the rows.
columns

Values to group by in the columns.
dnn

The names to be given to the dimensions in the result
deparse.level

Controls how the default dnn is constructed.
...

Any other parameters.

Value

Cross tabulation of the data

Lung Cancer Survival Data

Description

The lung dataset contains information about lung cancer survival.

Usage

lung

Format

A data frame with columns:

inst

institutional identification

time

Survival time in months.

status

Survival status (1 = death, 0 = censored).

age

Age of the patient at the start of the study.

sex

Gender of the patient.

ph.ecog

Performance status (Eastern Cooperative Oncology Group).

ph.karno

'Karnofsky' performance status.

pat.karno

'Karnofsky' performance status as assessed by the patient.

meal.cal

Daily caloric intake at the start of the study.

wt.loss

Weight loss in the last six months.

Examples

data(lung)

Nursery Database

Description

This dataset is originated from a hierarchical decision model created to evaluate applications for nursery schools.

Usage

nursery_data

Format

A data frame with columns: A data frame with 12960 rows and 9 columns:

parents

Parents' occupation

has_nurs

Child's nursery

form

Form of the family

children

Number of children

housing

Housing conditions

finance

Financial standing of the family

social

Social conditions

health

Health conditions

recommend

The ranking of applications for nursery schools

Source

https://www.openml.org/search?type=data&status=active&id=26&sort=runs

Examples

data(nursery_data)