Hypothesis testing of the ACE(t)-p models

Description

Comparison of different ACE(t)-p models to test a linear or a constant variance component.

Usage

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test_acetp(acetp, comp, sim = 100, robust = 0, pe = TRUE)

Arguments

acetp

An object from the AtCtEtp function.

comp

The component to test linearity or constant. The variance of this component must be dynamic or linear in the object from the AtCtEtp function.

sim

The number of the bootstrap resampling for approximating the null distribution when testing linearity.

robust

An integer indicating the number of different initial values that the function will randomly generate and try in the optimization. The default value is 0.

pe

A logical argument indicating whether to use penalized spline model to test linearity. The default value is TRUE.

Details

When pe=TRUE, the linearity is tested under a p-spline framework in which an LRT is performed. Otherwise, a χ^2 test is performed for linearity under a spline framework without penalty on smoothness.

Value

p

The p-value for the test.

llr

The LRT statistic for testing linearity.

llr_sim

The simulated null distribution of the LRT statistic for testing linearity.

chisq

The chisq statistic for testing a constant or linearity.

Author(s)

Liang He

References

He, L., Sillanpää, M.J., Silventoinen, K., Kaprio, J. and Pitkäniemi, J., 2016. Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models. Genetics, 202(4), pp.1313-1328.

Examples

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# data(data_ace)

# result <- AtCtEtp(data_ace$mz, data_ace$dz, knot_e = 7, knot_c = 5, mod=c('d','d','l'))
# re <- test_acetp(result, comp='e')