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Fit Delay-Discounting Model

Source: R/fitting.R
fit_dd.Rd

This function fits a delay-discounting model to the given dataset using the specified equation and method.

Usage

fit_dd(dat, equation, method)

Arguments

dat

A data frame containing delay (x) and indifference point (y) data. For "two stage" methods, the data must include an id column to identify participants.

equation

A character string specifying the delay-discounting equation to use. Options include:

  • "mazur" or "hyperbolic": Hyperbolic delay-discounting model (\(y = 1 / (1 + k \cdot x)\)).

  • "exponential": Exponential delay-discounting model (\(y = \exp(-k \cdot x)\)).

method

A character string specifying the method for fitting the model. Options include:

  • "pooled" or "agg": Fits the model using pooled data.

  • "mean": Fits the model using the mean of indifference points at each delay.

  • "ts" or "two stage": Fits the model separately for each participant (requires an id column in dat).

Value

A list object of class "fit_dd", containing:

  • The fitted model(s).

  • The original dataset (dat).

  • The specified method (method).

Examples

data <- data.frame(
  id = rep(1:2, each = 6),
  x = rep(c(1, 7, 30, 90, 180, 365), 2),
  y = c(0.9, 0.5, 0.3, 0.2, 0.1, 0.05, 0.85, 0.55, 0.35, 0.15, 0.1, 0.05)
)
fit_dd(data, equation = "mazur", method = "two stage")
#> [[1]]
#> [[1]]$`1`
#> [[1]]$`1`$result
#> Nonlinear regression model
#>   model: y ~ 1/(1 + k * x)
#>    data: data
#>      k 
#> 0.1008 
#>  residual sum-of-squares: 0.02315
#> 
#> Number of iterations to convergence: 10 
#> Achieved convergence tolerance: 1.49e-08
#> 
#> [[1]]$`1`$error
#> NULL
#> 
#> 
#> [[1]]$`2`
#> [[1]]$`2`$result
#> Nonlinear regression model
#>   model: y ~ 1/(1 + k * x)
#>    data: data
#>       k 
#> 0.08777 
#>  residual sum-of-squares: 0.01866
#> 
#> Number of iterations to convergence: 9 
#> Achieved convergence tolerance: 1.49e-08
#> 
#> [[1]]$`2`$error
#> NULL
#> 
#> 
#> 
#> [[2]]
#>    id   x    y
#> 1   1   1 0.90
#> 2   1   7 0.50
#> 3   1  30 0.30
#> 4   1  90 0.20
#> 5   1 180 0.10
#> 6   1 365 0.05
#> 7   2   1 0.85
#> 8   2   7 0.55
#> 9   2  30 0.35
#> 10  2  90 0.15
#> 11  2 180 0.10
#> 12  2 365 0.05
#> 
#> [[3]]
#> [1] "two stage"
#> 
#> attr(,"class")
#> [1] "fit_dd" "list"