apci.plot.hexagram {APCI}

Plot the hexagram heatmap

Description

Plot the cohort effect in the style of hexagram

Usage

apci.plot.hexagram(
  model,
  age,
  period,
  first_age,
  first_period,
  interval,
  first_age_isoline = NULL,
  first_period_isoline = NULL,
  isoline_interval = NULL,
  color_scale = NULL,
  color_map = NULL,
  line_width = 0.5,
  line_color = "grey",
  label_size = 0.5,
  label_color = "black",
  scale_units = "Quintile",
  wrap_cohort_labels = TRUE,
  quantile = NULL
)

Arguments

model

A list recording the results from function apci.

age

An object of class character representing the age group index taking on a small number of distinct values in the data. Usually, the vector should be converted to a factor (or the terms of "category" and "enumerated type").

period

An object of class character, similar to the argument of age, representing the time period index in the data.

first_age

The first age group.

first_period

The first period group.

interval

The width of age and period groups.

first_age_isoline

Isoline for the first age group.

first_period_isoline

Isoline for the first period group.

isoline_interval

Interval of isoline.

color_scale

A vector including two numbers indicating the limit of the values to be plotted. The first number is the minimum value to be visualized and the second is the maximum value to be visualized. If NULL, the algorithm will automatically select the limits from the data (estimation results) to set up the scale.

color_map

A vector, representing the color palettes to be used in the figure. The default setting is greys if color_map is NULL. Alternations, for example, can be c("blue", "yellow"), blues, etc.

line_width

Width of lines. Default is 0.5.

line_color

Line colors. Default is grey.

label_size

Axis label size. Default is 0.5.

label_color

Axis label color. Default is Black.

scale_units

Units of scales.

wrap_cohort_labels

Display the cohort label or not. The default is TRUE.

quantile

A number valued between 0 and 1, representing the desirable percentiles to be used in visualizing the data or model. If NULL, the original scale of the outcome variable will be used.

Value

A hexagram visualizing the APC-I model results.

Examples

# load package
library("APCI")
# load data
test_data <- APCI::women9017
test_data$acc <- as.factor(test_data$acc)
test_data$pcc <- as.factor(test_data$pcc)
test_data$educc <- as.factor(test_data$educc)
test_data$educr <- as.factor(test_data$educr)

# fit APC-I model
APC_I <- APCI::apci(outcome = "inlfc",
                    age = "acc",
                    period = "pcc",
                    cohort = "ccc",
                    weight = "wt",
                    data = test_data,dev.test=FALSE,
                    print = TRUE,
                    family = "gaussian")
summary(APC_I)

# plot hexagram
apci.plot.hexagram(model=APC_I,age="acc",period="pcc",first_age = 20,
                   first_period = 1940, interval = 5)