Calculates the penetrance for an individual based on Weibull distribution parameters. This function estimates the probability of developing cancer given the individual's genetic and demographic information.
Usage
lik.fn(
i,
data,
alpha_male,
alpha_female,
beta_male,
beta_female,
delta_male,
delta_female,
gamma_male,
gamma_female,
max_age,
baselineRisk,
BaselineNC
)Arguments
- i
Integer, index of the individual in the data set.
- data
Data frame, containing individual demographic and genetic information. Must include columns for 'sex', 'age', 'aff' (affection status), and 'geno' (genotype).
- alpha_male
Numeric, Weibull distribution shape parameter for males.
- alpha_female
Numeric, Weibull distribution shape parameter for females.
- beta_male
Numeric, Weibull distribution scale parameter for males.
- beta_female
Numeric, Weibull distribution scale parameter for females.
- delta_male
Numeric, shift parameter for the Weibull function for males.
- delta_female
Numeric, shift parameter for the Weibull function for females.
- gamma_male
Numeric, asymptote parameter for males (only scales the entire distribution).
- gamma_female
Numeric, asymptote parameter for females (only scales the entire distribution).
- max_age
Integer, maximum age considered in the analysis.
- baselineRisk
Numeric matrix, baseline risk for each age by sex. Rows correspond to sex (1 for male, 2 for female) and columns to age.
- BaselineNC
Logical, indicates if non-carrier penetrance should be based on SEER data.