biodosetools (version 3.7.2)

estimate_hetero_mixed_poisson: Heterogeneous dose estimation (Mixed Poisson model)

Description

Method based on the paper by Pujol, M. et al. (2016). A New Model for Biological Dose Assessment in Cases of Heterogeneous Exposures to Ionizing Radiation. Radiation Research, 185(2), 151-162. <doi:10.1667/RR14145.1>.

Usage

estimate_hetero_mixed_poisson(
  case_data,
  fit_coeffs,
  fit_var_cov_mat,
  conf_int = 0.95,
  protracted_g_value = 1,
  gamma,
  gamma_error
)

Value

List containing estimated mixing proportions data frame, estimated yields data frame, estimated doses data frame, estimated fraction of irradiated blood data frame, AIC, and conf_int_* used.

Arguments

case_data

Case data in data frame form.

fit_coeffs

Fitting coefficients matrix.

fit_var_cov_mat

Fitting variance-covariance matrix.

conf_int

Confidence interval, 95% by default.

protracted_g_value

Protracted \(G(x)\) value.

gamma

Survival coefficient of irradiated cells.

gamma_error

Error of the survival coefficient of irradiated cells.

Examples

#The fitting RDS result from the fitting module is needed. Alternatively, manual data
#frames that match the structure of the RDS can be used:


fit_coeffs <- data.frame(
  estimate   = c(0.001280319, 0.021038724, 0.063032534),
  std.error  = c(0.0004714055, 0.0051576170, 0.0040073856),
  statistic  = c(2.715961, 4.079156, 15.729091),
  p.value    = c(6.608367e-03, 4.519949e-05, 9.557291e-56),
  row.names =  c("coeff_C", "coeff_alpha", "coeff_beta")
)


fit_var_cov_mat <- data.frame(
  coeff_C      = c(2.222231e-07, -9.949044e-07,  4.379944e-07),
  coeff_alpha  = c(-9.949044e-07, 2.660101e-05, -1.510494e-05),
  coeff_beta   = c(4.379944e-07, -1.510494e-05, 1.605914e-05),
  row.names =  c("coeff_C", "coeff_alpha", "coeff_beta")
)


case_data <- data.frame(
  ID= "example1",
  N = 361,
  X = 100,
  C0 = 302,
  C1 = 28,
  C2 = 22,
  C3 = 8,
  C4 = 1,
  C5 = 0,
  y = 0.277,
  y_err = 0.0368,
  DI = 1.77,
  u = 10.4
)


#FUNCTION ESTIMATE_HETERO_MIXED_POISSON
estimate_hetero_mixed_poisson(
  case_data[1, ],
  fit_coeffs = as.matrix(fit_coeffs),
  fit_var_cov_mat = as.matrix(fit_var_cov_mat),
  conf_int = 0.95,
  protracted_g_value = 1,
  gamma = 1 / 2.7,
  gamma_error = 0
)