| Type: | Package |
| Title: | Tidy Tools for Joinpoint Regression Models |
| Version: | 0.5.0 |
| Description: | Provides tools to fit joinpoint regression models with a log-linear specification by levels of a categorical variable. The package acts as a wrapper around the 'segmented' package, facilitating model fitting, selection, and interpretation. It includes functions to estimate the Annual Percent Change (APC) and the Average Annual Percent Change (AAPC), along with their 95% confidence intervals, and to generate formatted summary tables and plots of results. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| Imports: | dplyr, purrr, tidyr, tibble, ggplot2, segmented, scales, flextable, rlang, stringr, stats, officer |
| RoxygenNote: | 7.3.3 |
| URL: | https://github.com/datos-ine/joinpointR |
| BugReports: | https://github.com/datos-ine/joinpointR/issues |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2026-04-29 14:58:19 UTC; user |
| Author: | Tamara Ricardo 
[aut, cre] |
| Maintainer: | Tamara Ricardo <tamararicardo83@gmail.com> |
| Depends: | R (≥ 4.1.0) |
| Repository: | CRAN |
| Date/Publication: | 2026-05-02 09:50:02 UTC |
Average Annual Percent Change (AAPC)
Description
Estimates the Average Annual Percent Change (AAPC) and its 95% confidence interval. Optionally displays statistical significance using significance stars.
Usage
get_aapc(mod, digits = 1, show_ci = TRUE, dec = ".")
Arguments
mod |
Joinpoint regression model (segmented object) or linear regression model (lm object). |
digits |
Number of decimal places to display (integer). |
show_ci |
Logical; if TRUE, displays the 95% confidence interval. If FALSE, displays significance stars. |
dec |
Character. Decimal separator to use (e.g., "." or ","). |
Value
A character string with the AAPC and either its 95% confidence interval or significance stars.
Author(s)
Tamara Ricardo
Examples
# Load example data
data("plant", package = "segmented")
names(plant)
# Fit the joinpoint models
mods <- model_jp(data = plant, value = "y", time = "time", group = "group", k = 2, test = TRUE)
# AAPC of the first model
get_aapc(mods$RKW, digits = 1, show_ci = TRUE, dec = ".")
Annual Percent Change by Segment (APC)
Description
Calculates the Annual Percent Change (APC) for each segment and its 95% confidence interval.
Usage
get_apc(mod, digits = 1, time = "time", dec = ".")
Arguments
mod |
Joinpoint regression model (segmented object). |
digits |
Number of decimal places to display (integer). |
time |
Time variable used in the model (character). |
dec |
Character. Decimal separator to use (e.g., "." or ","). |
Value
A character vector with APC and 95% CI for each segment.
Author(s)
Tamara Ricardo
Examples
# Load example data
data("plant", package = "segmented")
names(plant)
# Fit the joinpoint models
mods <- model_jp(data = plant, value = "y", time = "time", group = "group", k = 2, test = TRUE)
# Obtain APC (95% CI)
get_apc(mods$RKW, digits = 1, time = "time", dec = ".")
Plot Joinpoint Regression Models
Description
Creates a ggplot showing observed values, fitted joinpoint regression lines, and optional joinpoints.
Usage
gg_jpoint(mods, obs = TRUE, jp = TRUE, facets = FALSE)
Arguments
mods |
List of joinpoint regression models (output of model_jp()). |
obs |
Logical. If TRUE, displays observed data points. |
jp |
Logical. If TRUE, displays joinpoints as vertical dashed lines. |
facets |
Logical. If TRUE, displays one panel per group using facets. |
Value
A ggplot object.
Examples
library(dplyr)
# Load example data
data("plant", package = "segmented")
names(plant)
# Fit the joinpoint models
mods <- model_jp(data = plant, value = "y", time = "time", group = "group", k = 2, test = TRUE)
# Plot results
gg_jpoint(mods, obs = TRUE, jp = TRUE, facets = FALSE)
# Facets by group
gg_jpoint(mods, obs = TRUE, jp = TRUE, facets = TRUE)
Joinpoint Regression Models by Groups
Description
Fits segmented linear regression models by groups for age-standardized rates,
using a stepwise procedure based on the Bayesian Information Criterion (BIC).
Internally calls segmented::selgmented() and applies a log transformation
to the response variable.
Usage
model_jp(data, value, time, group, k = 2, test = TRUE)
Arguments
data |
Data frame containing age-standardized rates. |
value |
Response variable (character). |
time |
Time variable (character). |
group |
Grouping variable (character). |
k |
Maximum number of joinpoints (integer). |
test |
Test for differences in the t-values of the slope (logical). |
Value
A list of models by group.
Author(s)
Tamara Ricardo
Examples
# Generate example data
library(dplyr)
df <- mtcars |>
mutate(
year = seq(2000, length.out = n(), by = 1),
group = factor(paste("cyl", cyl, sep = "_")),
rate = mpg
) |>
select(year, group, rate)
# Check group levels
levels(df$group)
# Fit models
mods <- model_jp(data = df, value = "rate", time = "year", group = "group", k = 2, test = TRUE)
# Show the output of the first model
mods$cyl_6
summary(mods$cyl_6)
Summary Table For Joinpoint Regression Models
Description
Generates a table displaying the number of joinpoints, time breaks, APC and its 95% confidence interval, and AAPC and its statistical significance from a list of joinpoint models.
Usage
summary_jp(
mods,
digits = 1,
var1 = "group",
var2 = "subgroup",
ft = FALSE,
lan = c("en", "es")
)
Arguments
mods |
List of joinpoint regression models (model_jp() output). |
digits |
Number of decimal places to display (integer). |
var1 |
Character. Name of the grouping variable. |
var2 |
Character. Name of the subgrouping variable (optional). |
ft |
Logical. If TRUE returns a flextable object, if FALSE returns a tibble. |
lan |
Language of output: "en" (English) or "es" (Spanish). |
Value
A tibble or a flextable object.
Author(s)
Tamara Ricardo
Examples
library(dplyr)
# Load example data
data("plant", package = "segmented")
names(plant)
# Fit the joinpoint models
mods <- model_jp(data = plant, value = "y", time = "time", group = "group", k = 2, test = TRUE)
summary_jp(mods, digits = 1, var1 = "group", ft = FALSE, lan = "en")