The goal of pattern.checks
is to identify entries with patterned
responses for psychometric scales. The patterns included in the package
are:
- Identical responses: e.g.,
a, a, a
- Ascending responses: e.g.,
a, b, c
- Descending responses: e.g.,
c, b, a
- Alternative patterns: e.g.,
a, b, a, b
(ABAB) - Repeating sequences: e.g.,
a, b, c, a, b, c
(ABCABC)
You can install the development version of pattern.checks
like so:
# Install devtools if not already installed
install.packages("devtools")
# Use devtools to install the development version
devtools::install_github("JZL-CK/pattern.checks")
library(pattern.checks)
You can install the released version of pattern.checks
from
CRAN with:
install.packages("pattern.checks")
Here is a basic example demonstrating how to identify participants with a specific pattern in their responses:
library(pattern.checks)
# Example dataset
data <- data.frame(
V1 = c(1, 2, 3, 1, 1),
V2 = c(1, 3, 2, 1, 1),
V3 = c(1, 4, 1, 1, 1)
)
# Identify participants with identical responses across columns 1 to 3
result <- pattern.id(data, 1:3)
print(result)
#> $participants
#> [1] 1 4 5
#>
#> $responses
#> V1 V2 V3
#> 1 1 1 1
#> 4 1 1 1
#> 5 1 1 1
# Identify participants with responses in ascending order
result <- pattern.as(data, 1:3)
print(result)
#> $participants
#> [1] 2
#>
#> $responses
#> V1 V2 V3
#> 2 2 3 4
# Identify participants with responses in descending order
result <- pattern.ds(data, 1:3)
print(result)
#> $participants
#> [1] 3
#>
#> $responses
#> V1 V2 V3
#> 3 3 2 1
# Identify participants with ABAB pattern responses
result <- pattern.abab(data, 1:3)
print(result)
#> $participants
#> integer(0)
#>
#> $responses
#> [1] V1 V2 V3
#> <0 rows> (or 0-length row.names)
# Identify participants with ABCABC pattern responses
result <- pattern.abcabc(data, 1:3)
print(result)
#> $participants
#> [1] 2 3
#>
#> $responses
#> V1 V2 V3
#> 2 2 3 4
#> 3 3 2 1
Each function returns a list with two elements:
participants
: A vector of row indices for participants with the specified pattern.responses
: A data frame containing their responses for the specified columns.
For example, the output for pattern.id
might look like this:
$participants
[1] 1 4
$responses
V1 V2 V3
1 1 1 1
4 1 1 1
You can use these functions to systematically identify patterned responses in psychometric data and address potential response biases.
If you use the pattern.checks
package in your research, please cite it
as:
C K, J. (2025). pattern.checks: A package to identify patterned responses in psychometric scales. R package version 1.0. Available at: [GitHub Repository Link].
For any queries and suggestions, contact me via [email protected]