Linear model plot

Source: R/plot-pair-lm.R

This function is used in reliability and validity visualization

plot_pair_lm(
  predictor,
  outcome,
  SESOI_lower = 0,
  SESOI_upper = 0,
  confidence = 0.95,
  predictor_label = "Predictor",
  outcome_label = "Outcome",
  fitted_label = "Fitted",
  residuals_label = "Residuals",
  control = plot_control(),
  na.rm = FALSE
)

Arguments

predictor

Numeric vector
outcome

Vector
SESOI_lower

Lower smallest effect size of interest threshold
SESOI_upper

Upper smallest effect size of interest threshold
confidence

Default is 0.95
predictor_label

Character vector. The name of the predictor. Default is "Predictor"
outcome_label

Character vector. The name of the outcome. Default is "Outcome"
fitted_label

Character vector. The label to be used for fitted. Default is "Fitted"
residuals_label

Character vector. The label to be used for residuals. Default is "Residuals"
control

Plotting control object returned from plot_control
na.rm

Should NAs be removed? Default is FALSE

Value

ggplot object

See also

plot_pair_BA for Bland-Altman plot and plot_pair_OLP for ordinary-least-squares residuals plot

Examples

criterion <- rnorm(
  n = 100,
  mean = 100,
  sd = 10
)

practical <- criterion * 1.2 + rnorm(n = 100, mean = -12, sd = 5)

plot_pair_lm(practical,
  criterion,
  SESOI_lower = -10,
  SESOI_upper = 10,
  predictor_label = "Practical",
  outcome_label = "Criterion"
)