Test for differences in a cosinor model between levels of the grouping variable.
Source:R/test_cosinor.R
test_cosinor_levels.Rd
Given a time variable and optional covariates, generate inference a cosinor fit. For the covariate named (or vector of covariates), this function performs a Wald test comparing the group with covariates equal to 1 to the group with covariates equal to 0. This may not be the desired result for continuous covariates.
Usage
test_cosinor_levels(
x,
x_str,
param = "amp",
comparison_A,
comparison_B,
component_index = 1,
ci_level = 0.95
)
Arguments
- x
An
cglmm
object.- x_str
A
character
. The name of the grouping variable within which differences in the selected cosinor characteristic (amplitude or acrophase) will be tested.- param
A
character
. Either"amp"
or"acr"
for testing differences in amplitude or acrophase, respectively.- comparison_A
An
integer, or string
. Refers to the first level within the grouping variablex_str
that is to act as the reference group in the comparison. Ensure that it corresponds to the name of the level in the original dataset.- comparison_B
An
integer, or string
. Refers to the second level within the grouping variablex_str
that is to act as the comparator group in the comparison. Ensure that it corresponds to the name of the level in the original dataset.- component_index
An
integer
. Ifcomparison_type = "levels"
,component_index
indicates which component is being compared between the levels of the grouping variable.- ci_level
The level for calculated confidence intervals. Defaults to
0.95
.
Examples
data_2_component <- simulate_cosinor(
n = 10000,
mesor = 5,
amp = c(2, 5),
acro = c(0, pi),
beta.mesor = 4,
beta.amp = c(3, 4),
beta.acro = c(0, pi / 2),
family = "gaussian",
n_components = 2,
period = c(10, 12),
beta.group = TRUE
)
mod_2_component <- cglmm(
Y ~ group + amp_acro(times,
n_components = 2, group = "group",
period = c(10, 12)
),
data = data_2_component
)
test_cosinor_levels(mod_2_component, param = "amp", x_str = "group")
#> Test Details:
#> Parameter being tested:
#> Amplitude
#>
#> Comparison type:
#> levels
#>
#> Grouping variable used for comparison between groups: group
#> Reference group: 0
#> Comparator group: 1
#>
#> cglmm model has2 components. Component 1 is being used for comparison between groups.
#>
#>
#>
#> Global test:
#> Statistic:
#> 248.18
#>
#> P-value:
#> 0
#>
#>
#> Individual tests:
#> Statistic:
#> 15.75
#>
#> P-value:
#> 0
#>
#> Estimate and 95% confidence interval:
#> 1.02 (0.89 to 1.15)