Computes the analytic noncentrality parameter (NCP) for the likelihood-ratio test allowing for error (LRTae) in a prospective case-control design. The calculation incorporates fallible measurements and validation subsamples for phenotype, genotype, or both. It does not analyze observed study data.
lrtae_ncp(
true_control_genotype_frequencies,
true_case_genotype_frequencies,
true_sampling_proportions,
phenotype_misclassification_matrix,
genotype_misclassification_matrix,
n_fallible,
n_pheno_validated,
n_geno_validated,
n_both_validated
)Numeric vector of true genotype frequencies among controls.
Numeric vector of true genotype
frequencies among cases, in the same category order as
true_control_genotype_frequencies.
Numeric vector of length two containing the true control and case sampling proportions, in that order.
Numeric two-by-two matrix whose rows are true phenotype categories (control, case) and whose columns are observed phenotype categories (control, case).
Numeric square matrix whose rows are true genotype categories and whose columns are observed genotype categories, in the genotype-frequency order.
Number sampled with fallible phenotype and genotype measurements only.
Number whose phenotype is validated while genotype is measured fallibly.
Number whose genotype is validated while phenotype is measured fallibly.
Number whose phenotype and genotype are both validated.
A single nonnegative numeric value: the LRTae NCP.
Ji, F., Yang, Y., Haynes, C., Finch, S. J., & Gordon, D. (2005). Computing asymptotic power and sample size for case-control genetic association studies in the presence of phenotype and/or genotype misclassification errors. Statistical Applications in Genetics and Molecular Biology, 4(1), Article 37. doi:10.2202/1544-6115.1184
Barral, S., Haynes, C., Stone, M., & Gordon, D. (2006). LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present. BMC Genetics, 7, 24. doi:10.1186/1471-2156-7-24
Gordon, D., Finch, S. J., & Kim, W. (2020). Heterogeneity in Statistical Genetics: How to Assess, Address, and Account for Mixtures in Association Studies. Springer. doi:10.1007/978-3-030-61121-7
lrtae_ncp(
true_control_genotype_frequencies = c(0.81, 0.18, 0.01),
true_case_genotype_frequencies = c(0.64, 0.32, 0.04),
true_sampling_proportions = c(0.5, 0.5),
phenotype_misclassification_matrix = matrix(
c(0.95, 0.05, 0.05, 0.95), nrow = 2, byrow = TRUE
),
genotype_misclassification_matrix = matrix(
c(0.950, 0.050, 0.000,
0.025, 0.950, 0.025,
0.000, 0.050, 0.950),
nrow = 3, byrow = TRUE
),
n_fallible = 700,
n_pheno_validated = 100,
n_geno_validated = 100,
n_both_validated = 100
)
#> [1] 29.17305