The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Type: Package
Title: Survey Defense Tool
Version: 0.2.0
Description: This tool is designed to analyze up to 5 Fraud Detection Questions integrated into a survey, focusing on potential fraudulent participants to clean the survey dataset from potential fraud. Fraud Detection Questions and further information available at https://surveydefense.org.
License: GPL-3
Encoding: UTF-8
Depends: R (≥ 3.5.0)
Imports: dplyr, flextable, utils
Suggests: officer
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2024-09-11 08:18:24 UTC; brueggemann
Author: Philipp Brüggemann [aut, cre]
Maintainer: Philipp Brüggemann <philippbrueggemann@web.de>
Repository: CRAN
Date/Publication: 2024-09-11 08:40:01 UTC

Fraud Detection Analysis Tool 1

Description

This function analyzes survey data based on up to 5 Fraud Detection Questions and generates results in Word and HTML formats.

Usage

FraudDetec1(
  output_dir,
  data,
  FraudList,
  correct_answers = c(0, 0, 0, 0, 0),
  ...
)

Arguments

output_dir

Path specifying where the Word and HTML files will be saved.

data

The data frame containing all the survey data.

FraudList

A character vector of up to 5 Fraud Detection Questions.

correct_answers

A numeric vector representing correct answers for each question. Default is c(0, 0, 0, 0, 0).

...

Survey questions to be analyzed.

Value

A flextable object with the fraud detection analysis results. The results include summary statistics and metrics comparing responses from reliable and fraudulent participants.

Examples

if (requireNamespace("flextable", quietly = TRUE) && requireNamespace("officer", quietly = TRUE)) {
  library(flextable)
  library(officer)

  # Example data for fraud detection analysis
  Q1 <- c(4, 5, 3, 2, 5, 2)
  Q2 <- c(3, 4, 2, 5, 4, 3)
  Q3 <- c(5, 4, 3, 5, 4, 5)
  Q4 <- c(1, 2, 3, 4, 5, 2)
  Q5 <- c(5, 2, 2, 1, 4, 1)
  Q6 <- c(5, 2, 3, 5, 1, 2)
  Q7 <- c(5, 2, 4, 5, 3, 4)

  Fraud1 <- c(0, 1, 0, 0, 0, 0)
  Fraud2 <- c(0, 0, 0, 0, 0, 0)
  Fraud3 <- c(0, 1, 0, 0, 0, 0)
  Fraud4 <- c(0, 0, 1, 0, 0, 1)
  Fraud5 <- c(0, 0, 0, 1, 1, 1)

  Test_Data_Fraud <- data.frame(Q1, Q2, Q3, Q4, Q5, Q6, Q7, Fraud1, Fraud2, Fraud3, Fraud4, Fraud5)

  temp_dir <- tempdir()

  FraudDetec1(
    output_dir = temp_dir,
    data = Test_Data_Fraud,
    FraudList = c("Fraud1", "Fraud2", "Fraud3", "Fraud4", "Fraud5"),
    correct_answers = c(0, 0, 0, 0, 0),
    Q1, Q2, Q3, Q4, Q5, Q6, Q7
  )
}

Fraud Detection Analysis Tool 2

Description

This function analyzes survey data using up to 5 Fraud Detection Questions and generates a report in Word and HTML formats.

Usage

FraudDetec2(
  output_dir,
  data,
  FraudList,
  correct_answers = c(0, 0, 0, 0, 0),
  ...
)

Arguments

output_dir

Path specifying where the Word and HTML files will be saved.

data

The data frame containing all the survey data.

FraudList

A character vector of up to 5 Fraud Detection Questions.

correct_answers

A numeric vector representing correct answers for each question. Default is c(0, 0, 0, 0, 0).

...

Survey questions to be analyzed.

Value

A flextable object with the fraud detection analysis results, including summary statistics for the overall sample and identified fraudulent responses.

Examples

if (requireNamespace("flextable", quietly = TRUE) && requireNamespace("officer", quietly = TRUE)) {
  library(flextable)
  library(officer)

  # Example data for fraud detection analysis
  Q1 <- c(4, 5, 3, 2, 5, 2)
  Q2 <- c(3, 4, 2, 5, 4, 3)
  Q3 <- c(5, 4, 3, 5, 4, 5)
  Q4 <- c(1, 2, 3, 4, 5, 2)
  Q5 <- c(5, 2, 2, 1, 4, 1)
  Q6 <- c(5, 2, 3, 5, 1, 2)
  Q7 <- c(5, 2, 4, 5, 3, 4)

  Fraud1 <- c(0, 1, 0, 0, 0, 0)
  Fraud2 <- c(0, 0, 0, 0, 0, 0)
  Fraud3 <- c(0, 1, 0, 0, 0, 0)
  Fraud4 <- c(0, 0, 1, 0, 0, 1)
  Fraud5 <- c(0, 0, 0, 1, 1, 1)

  Test_Data_Fraud <- data.frame(Q1, Q2, Q3, Q4, Q5, Q6, Q7, Fraud1, Fraud2, Fraud3, Fraud4, Fraud5)

  temp_dir <- tempdir()

  FraudDetec2(
    output_dir = temp_dir,
    data = Test_Data_Fraud,
    FraudList = c("Fraud1", "Fraud2", "Fraud3", "Fraud4", "Fraud5"),
    correct_answers = c(0, 0, 0, 0, 0),
    Q1, Q2, Q3, Q4, Q5, Q6, Q7
  )
}

Fraud Detection Analysis Tool 3

Description

Fraud Detection Analysis Tool 3

Usage

FraudDetec3(
  output_dir,
  data,
  FraudList,
  correct_answers = c(0, 0, 0, 0, 0),
  ...
)

Arguments

output_dir

Path specifying where the Word and HTML files will be saved.

data

The data frame containing all the survey data.

FraudList

A character vector of up to 5 Fraud Detection Questions.

correct_answers

A numeric vector representing correct answers for each question. Default is c(0, 0, 0, 0, 0).

...

Survey questions to be analyzed.

Value

A flextable object with the results.

Examples

if (requireNamespace("flextable", quietly = TRUE) && requireNamespace("officer", quietly = TRUE)) {
  library(flextable)
  library(officer)

  # Example data for fraud detection analysis
  Q1 <- c(4, 5, 3, 2, 5, 2)
  Q2 <- c(3, 4, 2, 5, 4, 3)
  Q3 <- c(5, 4, 3, 5, 4, 5)
  Q4 <- c(1, 2, 3, 4, 5, 2)
  Q5 <- c(5, 2, 2, 1, 4, 1)
  Q6 <- c(5, 2, 3, 5, 1, 2)
  Q7 <- c(5, 2, 4, 5, 3, 4)

  Fraud1 <- c(0, 1, 0, 0, 0, 0)
  Fraud2 <- c(0, 0, 0, 0, 0, 0)
  Fraud3 <- c(0, 1, 0, 0, 0, 0)
  Fraud4 <- c(0, 0, 1, 0, 0, 1)
  Fraud5 <- c(0, 0, 0, 1, 1, 1)

  Test_Data_Fraud <- data.frame(Q1, Q2, Q3, Q4, Q5, Q6, Q7, Fraud1, Fraud2, Fraud3, Fraud4, Fraud5)

  temp_dir <- tempdir()

  FraudDetec3(
    output_dir = temp_dir,
    data = Test_Data_Fraud,
    FraudList = c("Fraud1", "Fraud2", "Fraud3", "Fraud4", "Fraud5"),
    correct_answers = c(0, 0, 0, 0, 0),
    Q1, Q2, Q3, Q4, Q5, Q6, Q7
  )
}

Fraud Detection Analysis Tool 4

Description

Fraud Detection Analysis Tool 4

Usage

FraudDetec4(
  output_dir,
  data,
  FraudList,
  correct_answers = c(0, 0, 0, 0, 0),
  ...
)

Arguments

output_dir

Path specifying where the Word and HTML files will be saved.

data

The data frame containing all the survey data.

FraudList

A character vector of up to 5 Fraud Detection Questions.

correct_answers

A numeric vector representing correct answers for each question. Default is c(0, 0, 0, 0, 0).

...

Survey questions to be analyzed.

Value

A flextable object with the results.

Examples

if (requireNamespace("flextable", quietly = TRUE) && requireNamespace("officer", quietly = TRUE)) {
  library(flextable)
  library(officer)

  # Example data for fraud detection analysis
  Q1 <- c(4, 5, 3, 2, 5, 2)
  Q2 <- c(3, 4, 2, 5, 4, 3)
  Q3 <- c(5, 4, 3, 5, 4, 5)
  Q4 <- c(1, 2, 3, 4, 5, 2)
  Q5 <- c(5, 2, 2, 1, 4, 1)
  Q6 <- c(5, 2, 3, 5, 1, 2)
  Q7 <- c(5, 2, 4, 5, 3, 4)

  Fraud1 <- c(0, 1, 0, 0, 0, 0)
  Fraud2 <- c(0, 0, 0, 0, 0, 0)
  Fraud3 <- c(0, 1, 0, 0, 0, 0)
  Fraud4 <- c(0, 0, 1, 0, 0, 1)
  Fraud5 <- c(0, 0, 0, 1, 1, 1)

  Test_Data_Fraud <- data.frame(Q1, Q2, Q3, Q4, Q5, Q6, Q7, Fraud1, Fraud2, Fraud3, Fraud4, Fraud5)

  temp_dir <- tempdir()

  FraudDetec4(
    output_dir = temp_dir,
    data = Test_Data_Fraud,
    FraudList = c("Fraud1", "Fraud2", "Fraud3", "Fraud4", "Fraud5"),
    correct_answers = c(0, 0, 0, 0, 0),
    Q1, Q2, Q3, Q4, Q5, Q6, Q7
  )
}

Fraud Detection Analysis Tool 5

Description

Fraud Detection Analysis Tool 5

Usage

FraudDetec5(
  output_dir,
  data,
  FraudList,
  correct_answers = c(0, 0, 0, 0, 0),
  ...
)

Arguments

output_dir

Path specifying where the Word and HTML files will be saved.

data

The data frame containing all the survey data.

FraudList

A character vector of up to 5 Fraud Detection Questions.

correct_answers

A numeric vector representing correct answers for each question. Default is c(0, 0, 0, 0, 0).

...

Survey questions to be analyzed.

Value

A flextable object with the results.

Examples

if (requireNamespace("flextable", quietly = TRUE) && requireNamespace("officer", quietly = TRUE)) {
  library(flextable)
  library(officer)

  # Example data for fraud detection analysis
  Q1 <- c(4, 5, 3, 2, 5, 2)
  Q2 <- c(3, 4, 2, 5, 4, 3)
  Q3 <- c(5, 4, 3, 5, 4, 5)
  Q4 <- c(1, 2, 3, 4, 5, 2)
  Q5 <- c(5, 2, 2, 1, 4, 1)
  Q6 <- c(5, 2, 3, 5, 1, 2)
  Q7 <- c(5, 2, 4, 5, 3, 4)

  Fraud1 <- c(0, 1, 0, 0, 0, 0)
  Fraud2 <- c(0, 0, 0, 0, 0, 0)
  Fraud3 <- c(0, 1, 0, 0, 0, 0)
  Fraud4 <- c(0, 0, 1, 0, 0, 1)
  Fraud5 <- c(0, 0, 0, 1, 1, 1)

  Test_Data_Fraud <- data.frame(Q1, Q2, Q3, Q4, Q5, Q6, Q7, Fraud1, Fraud2, Fraud3, Fraud4, Fraud5)

  temp_dir <- tempdir()

  FraudDetec5(
    output_dir = temp_dir,
    data = Test_Data_Fraud,
    FraudList = c("Fraud1", "Fraud2", "Fraud3", "Fraud4", "Fraud5"),
    correct_answers = c(0, 0, 0, 0, 0),
    Q1, Q2, Q3, Q4, Q5, Q6, Q7
  )
}

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.