biodosetools (version 3.7.2)

estimate_whole_body_merkle: Whole-body dose estimation (Merkle's method)

Description

Method based on the paper by Merkle, W. (1983). Statistical methods in regression and calibration analysis of chromosome aberration data. Radiation and Environmental Biophysics, 21(3), 217-233. <doi:10.1007/BF01323412>.

Usage

estimate_whole_body_merkle(
  num_cases,
  case_data,
  fit_coeffs,
  fit_var_cov_mat,
  conf_int_yield = 0.83,
  conf_int_curve = 0.83,
  protracted_g_value = 1,
  genome_factor = 1,
  aberr_module = c("dicentrics", "translocations", "micronuclei")
)

Value

List containing estimated doses data frame, AIC, and conf_int_* used.

Arguments

num_cases

number of cases.

case_data

Case data in data frame form.

fit_coeffs

Fitting coefficients matrix.

fit_var_cov_mat

Fitting variance-covariance matrix.

conf_int_yield

Confidence interval of the yield, 83% by default.

conf_int_curve

Confidence interval of the curve, 83% by default.

protracted_g_value

Protracted \(G(x)\) value.

genome_factor

Genomic conversion factor used in translocations, else 1.

aberr_module

Aberration module.

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_WHOLE_BODY_MERKLE
estimate_whole_body_merkle(
  num_cases = 1,
  case_data = case_data,
  fit_coeffs = as.matrix(fit_coeffs),
  fit_var_cov_mat = as.matrix(fit_var_cov_mat),
  conf_int_yield = 0.83,
  conf_int_curve = 0.83,
  protracted_g_value = 1,
  aberr_module = "dicentrics"
)