HWEintrinsic (version 1.2.3)

Lindley: Lindley (1988) Two Alleles Data

Description

Four samples of \(n = 100\) genotype counts previously discussed in previously analyzed by Lindley (1988). For the first three sets, the classical "exact" test rejects the null hypothesis of Hardy-Weinberg equilibrium with significance level below 3.4%, whereas for the last data set the Hardy-Weinberg model is not rejected, its p-value being around 20%.

Usage

data(Lindley)

Format

Four objects of class HWEdata.

References

Consonni, G., Moreno, E., and Venturini, S. (2011). "Testing Hardy-Weinberg equilibrium: an objective Bayesian analysis". Statistics in Medicine, 30, 62--74. https://onlinelibrary.wiley.com/doi/10.1002/sim.4084/abstract Guo, S.W. and Thompson, E.A. (1992), "Performing the Exact Test of Hardy-Weinberg Proportion for Multiple Alleles". Biometrics, 49, 361--372. Lindley D.V. (1988), "Statistical inference concerning Hardy-Weinberg equilibrium". In: Bernardo, J.M., DeGroot, M.H., Lindley, D.V. and Smith, A.F.M. (eds.), "Bayesian statistics 3". Oxford University Press, 307--326.

Examples

if (FALSE) {
# ATTENTION: the following code may take a long time to run! #

data(Lindley)
hwe.ibf.exact <- Vectorize(hwe.ibf, "t")
f <- seq(.05, 1, .05)
n <- sum([e-mail], na.rm = TRUE)

# Dataset 1 #
plot(dataL1)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL1))
npp.std <- 1/(1 + hwe.bf(dataL1))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
	ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")

# Dataset 2 #
plot(dataL2)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL2))
npp.std <- 1/(1 + hwe.bf(dataL2))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
	ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")

# Dataset 3 #
plot(dataL3)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL3))
npp.std <- 1/(1 + hwe.bf(dataL3))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
	ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")

# Dataset 4 #
plot(dataL4)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL4))
npp.std <- 1/(1 + hwe.bf(dataL4))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
	ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")
}