The goal of matriz
is to help you easily generate and
manage structured literature review matrices in R. The package aims to
streamline your research synthesis, track key study details, and
organize citations efficiently.
You can install the development version of matriz like so:
::install_github("jpmonteagudo28/matriz) devtools
or you can download it from CRAN:
install.packages("matriz")
This document walks through the main steps of using
matriz
, from setting up your matrix to searching and
refining it.
The first step is to bring your literature data into R. If you have
an existing matrix in CSV or another format, use the
import_matrix()
function. Otherwise, create an empty matrix
using init_matrix()
:
library(matriz)
#>
#> Attaching package: 'matriz'
#> The following object is masked from 'package:base':
#>
#> truncate
<- init_matrix()
lit_matrix
# Get matriz structure to guide in creating records
matriz_names()
#> class
#> year numeric
#> citation character
#> keywords character
#> profession character
#> electronic logical
#> purpose character
#> study_design character
#> outcome_var character
#> predictor_var character
#> sample numeric
#> dropout_rate numeric
#> setting character
#> inclusion_criteria character
#> ethnicity character
#> age numeric
#> sex factor
#> income factor
#> education character
#> measures character
#> analysis character
#> results character
#> limitations character
#> implications character
#> ethical_concerns character
#> biases character
#> notes character
# Start filling out individual record with article info
<- data.frame(year = 2025,
article citation = " ",
keywords = " ",
profession = "underwater basket weaver",
electronic = "YES",
purpose = "To investigate the depth of the oceans and retireve weaving materials",
study_design = "ethnography",
outcome_var = "perceived attitudes towards basket weaving",
predictor_var = NA,
sample = "a small school of clown fish",
setting = "Italy",
drop_rate = 0.13,
inclusion_criteria = "clow fish in Adriatic Sea",
ehtnicity = "oceanic",
age = "0 - 1 year",
sex = "both",
income = " ",
education = "none",
measures = "perceived attitudes",
analysis = "qualitative",
results = "no significant differences",
limitations = "small sample size",
implications = "clow fish don't like humans taking their homes for their own basket weaving endeavors",
ethical_concerns = "no informed consent given to school of clown fish",
biases = "clownfish always try to be funny. Lack of seriounness",
notes = "more research needed")
# Process and add the citation to the current record
<- system.file("examples","example.bib",package = "matriz")
bibtex
<- process_citation(article,bibtex)
cited_article
# Add the record to the literature matrix
<- add_record(lit_matrix, cited_article, .before = 1)
lit_matrix
# Update record if mistake was made
<- update_record(lit_matrix, notes, where = year == 2025, set_to = "actually, the clow fish don't want us to come back.") lit_matrix
If you have multiple literature matrices and need to combine them,
use merge_matrix()
. This function ensures that duplicate
columns are removed before merging.
Note: If your article summaries are lists and their element classes differ from those in the init_matrix data frame, using add_batch_record() may coerce all elements to lists instead of preserving their original classes.
# Merge two literature matrices by a common column (e.g., "study_id")
<- lit_matrix
additional_matrix <- merge_matrix(lit_matrix, additional_matrix, by = "year", all = TRUE)
combined_matrix #> Removing duplicate columns...
# if you rather bind the two matrices together by rows, use 'add_batch_record()'
<- add_batch_record(lit_matrix, additional_matrix) lit_matrix
Once your matrix is set up, you might need to search for specific
studies based on keywords, author names, or topics. Use
search_record()
to filter the matrix for relevant
entries.
Once you’ve refined and categorized your literature review, you can
export the matrix for further use in Excel or other tools using
export_matrix()
.
This structured workflow should make managing literature reviews more efficient and streamlined.