Download a copy of the vignette to follow along here: data_list.Rmd
This vignette outlines the importance, structure, and creation of the
data_list object. You can find much of this info by running
?generate_data_list
after loading the metasnf package.
The data_list is the main object used in the metasnf package to store data. It is a named and nested list containing input dataframes (data), the name of that input dataframe (for the user’s reference), the ‘domain’ of that dataframe (the broader source of information that the input dataframe is capturing, determined by user’s domain knowledge), and the type of feature stored in the dataframe (continuous, discrete, ordinal, categorical, or mixed).
Some examples of data_list generation and usage are below:
library(metasnf)
# Preparing some mock data
heart_rate_df <- data.frame(
patient_id = c("1", "2", "3"),
var1 = c(0.04, 0.1, 0.3),
var2 = c(30, 2, 0.3)
)
personality_test_df <- data.frame(
patient_id = c("1", "2", "3"),
var3 = c(900, 1990, 373),
var4 = c(509, 2209, 83)
)
survey_response_df <- data.frame(
patient_id = c("1", "2", "3"),
var5 = c(1, 3, 3),
var6 = c(2, 3, 3)
)
city_df <- data.frame(
patient_id = c("1", "2", "3"),
var7 = c("toronto", "montreal", "vancouver")
)
# Generating a data_list explicitly (Name each nested list element):
data_list <- generate_data_list(
list(
data = heart_rate_df,
name = "heart_rate",
domain = "clinical",
type = "continuous"
),
list(
data = personality_test_df,
name = "personality_test",
domain = "surveys",
type = "continuous"
),
list(
data = survey_response_df,
name = "survey_response",
domain = "surveys",
type = "ordinal"
),
list(
data = city_df,
name = "city",
domain = "location",
type = "categorical"
),
uid = "patient_id"
)
# Achieving the same result compactly:
data_list <- generate_data_list(
list(heart_rate_df, "heart_rate", "clinical", "continuous"),
list(personality_test_df, "personality_test", "surveys", "continuous"),
list(survey_response_df, "survey_response", "surveys", "ordinal"),
list(city_df, "city", "location", "categorical"),
uid = "patient_id"
)
# Printing data_list summaries
summarize_dl(data_list)
## name type domain length width
## 1 heart_rate continuous clinical 3 3
## 2 personality_test continuous surveys 3 3
## 3 survey_response ordinal surveys 3 3
## 4 city categorical location 3 2
Depending on your data preprocessing, it may be more convenient to
you to assemble the components of your data_list in an automated way and
then provide that result to generate_data_list
.
For example, your code could have generated a list like the one below:
list_of_lists <- list(
list(heart_rate_df, "data1", "domain1", "continuous"),
list(personality_test_df, "data2", "domain2", "continuous")
)
If generate_data_list
receives only a single list, it’ll
treat that list as containing all the components required to construct a
properly formatted data_list:
## name type domain length width
## 1 data1 continuous domain1 3 3
## 2 data2 continuous domain2 3 3