error_prop | R Documentation |
This function uses error propagation formulas for quantities computed from regression coefficients to estimate the error for all regression coefficients.
error_prop(
data_obj,
pairscan_obj,
perm = FALSE,
verbose = FALSE,
run_parallel = FALSE,
n_cores = 4,
just_m = FALSE
)
data_obj |
a |
pairscan_obj |
a pairscan object from |
perm |
A logical value to indicate whether error propagation should be performed on the test statistics (FALSE) or the permuted test statistics (TRUE). |
verbose |
A logical value to indicate whether the progress of the function should be printed to the screen. |
run_parallel |
boolean, default = FALSE |
n_cores |
The number of cores to use if run_parallel is TRUE, default = 4 |
just_m |
If TRUE only the m12 and m21 values are calculated. If FALSE, the default, the standard deviations are also calculated. |
This function returns the data object with a new list element: var_to_var_influences
if perm is set to FALSE and var_to_var_influences_perm if perm is set to TRUE. These tables
include the errors calculated for the marker1 to marker2 (m21) influences as well as the
marker2 to marker1 (m12) influences. These results are used by calc_p
to
calculate empirical p values.
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