| Type: | Package |
| Title: | Summary Statistics for Panel Data |
| Version: | 0.1.0 |
| Depends: | R (≥ 3.2.0), knitr, magrittr, rlang, plm |
| Imports: | dplyr, kableExtra, sampleSelection |
| Author: | Joao Claudio Macosso |
| Maintainer: | Joao Claudio Macosso <joaoclaudiomacosso@gmail.com> |
| URL: | https://github.com/Macosso/xtsum |
| BugReports: | https://github.com/Macosso/xtsum/issues |
| VignetteBuilder: | knitr |
| Description: | Based on 'STATA' xtsum command, it is used to compute summary statistics for a panel data set. It generates overall, between-group, and within-group statistics for specified variables in a panel data set, as presented in S. Porter (2023) https://stephenporter.org/files/xtsum_handout.pdf, StataCorp (2023) https://www.stata.com/manuals/xtxtsum.pdf. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2023-12-07 14:48:54 UTC; Joaoc |
| Repository: | CRAN |
| Date/Publication: | 2023-12-07 16:20:02 UTC |
Compute the maximum between-group
Description
This function calculates the maximum between-group in a panel data.
Usage
between_max(data, variable, id = NULL, t = NULL, na.rm = FALSE)
Arguments
data |
A data.frame or pdata.frame object containing the panel data. |
variable |
The variable for which the maximum between-group effect is calculated. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical. Should missing values be removed? Default is FALSE. |
Value
The maximum between-group effect.
Examples
# Example using pdata.frame
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
between_max(Gas, variable = "lgaspcar")
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
between_max(Crime, variable = "crmrte", id = "county", t = "year")
Compute the minimum between-group
Description
This function calculates the minimum between-group of a panel data.
Usage
between_min(data, variable, id = NULL, t = NULL, na.rm = FALSE)
Arguments
data |
A data.frame or pdata.frame object containing the panel data. |
variable |
The variable for which the minimum between-group effect is calculated. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical. Should missing values be removed? Default is FALSE. |
Value
The minimum between-group effect.
Examples
# Example using pdata.frame
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
between_min(Gas, variable = "lgaspcar")
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
between_min(Crime, variable = "crmrte", id = "county", t = "year")
Compute the standard deviation of between-group
Description
This function calculates the standard deviation of between-group in a panel data.
Usage
between_sd(data, variable, id = NULL, t = NULL, na.rm = FALSE)
Arguments
data |
A data.frame or pdata.frame object containing the panel data. |
variable |
The variable for which the standard deviation of between-group effects is calculated. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical. Should missing values be removed? Default is FALSE. |
Value
The standard deviation of between-group effects.
Examples
# Example using pdata.frame
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
between_sd(Gas, variable = "lgaspcar")
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
between_sd(Crime, variable = "crmrte", id = "county", t = "year")
Compute the maximum within-group for a panel data
Description
This function computes the maximum within-group for a panel data.
Usage
within_max(data, variable, id = NULL, t = NULL, na.rm = FALSE)
Arguments
data |
A data.frame or pdata.frame object containing the panel data. |
variable |
The variable for which the maximum within-group effect is calculated. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical. Should missing values be removed? Default is FALSE. |
Value
The maximum within-group effect.
Examples
# Example using pdata.frame
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
within_max(Gas, variable = "lgaspcar")
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
within_max(Crime, variable = "crmrte", id = "county", t = "year")
Compute the minimum within-group for panel data
Description
This function computes the minimum within-group for a panel data.
Usage
within_min(data, variable, id = NULL, t = NULL, na.rm = FALSE)
Arguments
data |
A data.frame or pdata.frame object containing the panel data. |
variable |
The variable for which the minimum within-group effect is calculated. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical. Should missing values be removed? Default is FALSE. |
Value
The minimum within-group effect.
Examples
# Example using pdata.frame
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
within_min(Gas, variable = "lgaspcar")
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
within_min(Crime, variable = "crmrte", id = "county", t = "year")
Compute the standard deviation of within-group for a panel data
Description
This function computes the standard deviation of within-group for a panel data.
Usage
within_sd(data, variable, id = NULL, t = NULL, na.rm = FALSE)
Arguments
data |
A data.frame or pdata.frame object containing the panel data. |
variable |
The variable for which the standard deviation of within-group effects is calculated. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical. Should missing values be removed? Default is FALSE. |
Value
The standard deviation of within-group effects.
Examples
# Example using pdata.frame
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
within_sd(Gas, variable = "lgaspcar")
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
within_sd(Crime, variable = "crmrte", id = "county", t = "year")
Calculate summary statistics for panel data
Description
This function computes summary statistics for panel data, including overall statistics, between-group statistics, and within-group statistics.
Usage
xtsum(
data,
variables = NULL,
id = NULL,
t = NULL,
na.rm = FALSE,
return.data.frame = FALSE,
dec = 3
)
Arguments
data |
A data.frame or pdata.frame object representing panel data. |
variables |
(Optional) Vector of variable names for which to calculate statistics. If not provided, all numeric variables in the data will be used. |
id |
(Optional) Name of the individual identifier variable. |
t |
(Optional) Name of the time identifier variable. |
na.rm |
Logical indicating whether to remove NAs when calculating statistics. |
return.data.frame |
If the return object should be a dataframe |
dec |
Number of significant digits to report |
Value
A table summarizing statistics for each variable, including Mean, SD, Min, and Max, broken down into Overall, Between, and Within dimensions.
Examples
# Using a data.frame and specifying variables, id, it, na.rm, dec
data("nlswork", package = "sampleSelection")
xtsum(nlswork, "hours", id = "idcode", t = "year", na.rm = TRUE, dec = 6)
# Using pdata.frame object without specifying a variable
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
xtsum(Gas)
# Using regular data.frame with id and t specified
data("Crime", package = "plm")
xtsum(Crime, variables = c("crmrte", "prbarr"), id = "county", t = "year")
# Specifying variables to include in the summary
xtsum(Gas, variables = c("lincomep", "lgaspcar"))