| 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 |
... |
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 |
... |
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 |
... |
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 |
... |
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 |
... |
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
)
}