Create a mixed effects model from an mmkin row object

Usage

mixed(object, ...)

# S3 method for mmkin
mixed(object, method = c("none"), ...)

# S3 method for mixed.mmkin
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

object: An mmkin row object
...: Currently not used
method: The method to be used
x: A mixed.mmkin object to print
digits: Number of digits to use for printing.

Value

An object of class 'mixed.mmkin' which has the observed data in a single dataframe which is convenient for plotting

Examples

sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
n_biphasic <- 8
err_1 = list(const = 1, prop = 0.07)

DFOP_SFO <- mkinmod(
  parent = mkinsub("DFOP", "m1"),
  m1 = mkinsub("SFO"),
  quiet = TRUE)

set.seed(123456)
log_sd <- 0.3
syn_biphasic_parms <- as.matrix(data.frame(
  k1 = rlnorm(n_biphasic, log(0.05), log_sd),
  k2 = rlnorm(n_biphasic, log(0.01), log_sd),
  g = plogis(rnorm(n_biphasic, 0, log_sd)),
  f_parent_to_m1 = plogis(rnorm(n_biphasic, 0, log_sd)),
  k_m1 = rlnorm(n_biphasic, log(0.002), log_sd)))

ds_biphasic_mean <- lapply(1:n_biphasic,
  function(i) {
    mkinpredict(DFOP_SFO, syn_biphasic_parms[i, ],
      c(parent = 100, m1 = 0), sampling_times)
  }
)

set.seed(123456L)
ds_biphasic <- lapply(ds_biphasic_mean, function(ds) {
  add_err(ds,
    sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),
    n = 1, secondary = "m1")[[1]]
})

# \dontrun{
f_mmkin <- mmkin(list("DFOP-SFO" = DFOP_SFO), ds_biphasic, error_model = "tc", quiet = TRUE)

f_mixed <- mixed(f_mmkin)
print(f_mixed)
#> Kinetic model fitted by nonlinear regression to each dataset
#> Structural model:
#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
#>            * parent
#> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
#>            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
#>            exp(-k2 * time))) * parent - k_m1 * m1
#> 
#> Data:
#> 271 observations of 2 variable(s) grouped in 8 datasets
#> 
#> <mmkin> object
#> Status of individual fits:
#> 
#>           dataset
#> model      1  2  3  4  5  6 7  8 
#>   DFOP-SFO OK OK OK OK OK C OK OK
#> 
#> C: Optimisation did not converge:
#> iteration limit reached without convergence (10)
#> OK: No warnings
#> 
#> Mean fitted parameters:
#>        parent_0        log_k_m1 f_parent_qlogis          log_k1          log_k2 
#>      100.605312       -8.758664       -0.001917       -3.350887       -3.990017 
#>        g_qlogis 
#>       -0.091167 
plot(f_mixed)

# }