apci.plot {APCI}

Plotting age and period raw scores and APC-I model results

Description

Arranging data exploration and model results representation in a harmonized way.

Usage

apci.plot(
  model,
  age,
  period,
  outcome_var,
  type = "model",
  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.

outcome_var

An object of class character indicating the name of the outcome variable used in the model. The outcome variable can be a continuous, binary, categorical, or count variable.

type

Character, "explore" or "model". If type is "explore", plots for age and period raw scores will be generated. If type is "model", model results will be plotted. The default setting is "model".

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.

...

Additional arguments to be passed to the function.

Value

A plot with three panels showing the raw scores or 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 the raw pattern
apci.plot(data = test_data, outcome_var = "inlfc", age = "acc",model=APC_I,
          period = "pcc", type = "explore")
## plot the model results
apci.plot(data = test_data, outcome_var = "inlfc", age = "acc",model=APC_I,
          period = "pcc", type = "model")