A specialized subclass of the FamModelFit abstract class for
linear mixed model results. Methods of this subclass can be used to print
model results in a nice format, access model objects, perform inference on
general contrasts, and perform likelihood ratio tests on variance
parameters. Due to reliance on the internal structures of other objects,
the object generator function is not exported, and instances of the
FamLMMFit class can be initizalized only from within functions in the
FamModel namespace.
FamModel::FamModelFit -> FamLMMFit
new()Constructs a new instance of this class
FamLMMFit$new(data, formula, objfun, optres)
dataThe FamData object that produced this model
fit.
formulaThe Formula::Formula object that describes
the model.
objfunA TMB::MakeADFun() object that has already been run
through an optimizer. This object is expected to have a "type"
attribute of "LMM-SA".
optresA list from the optimizer function detailing results.
This list is expected to have an attribute "opttype" that contains a
string identifying the function used for optimization.
Due to their reliance on the internal structures of other
objects, instances of the FamLMMFit class can be initizalized only
from within functions in the FamModel namespace.
get_formula()Returns the Formula::Formula object used to construct
the instance.
FamLMMFit$get_formula()
get_model_res()Returns the original data with fitted values, residuals, and diagnostics.
FamLMMFit$get_model_res(all = FALSE)
allIf FALSE (default), include only observations that
contributed to the model fit. If TRUE, include all observations in
the FamData object data member. This can be useful for
generating a data set to refit the model without certain outliers.
Fitted values, residuals, and diagnostics columns will have NA
values for observations that did not contribute to the model fit.
See vignette("linear_mixed_models") for a detailed
description of each residual and diagnostic, suggestions for its use,
and relevant references.
A data.table containing the data member of the
FamData object used to fit this model with the following
additional columns (notation defined in
vignette("linear_mixed_models")):
mu_hat: The fitted population mean, \(\hat{\mu}_{ij}\).
eta_hat: The mean conditional upon the data in the proband,
\(\hat{\eta}_{ij}\). These are defined for family members
(\(j \neq j_i\)) only and are NA in the proband.
r_c_hat: The estimated Cholesky residuals,
\(\hat{r}_{\mathrm{c}, ij}\). These are defined for family members
(\(j \neq j_i\)) only and are NA in the proband.
r_s_hat: The estimated Pearson-type conditional residuals,
\(\hat{r}_{\mathrm{s}, ij}\). These are defined for family members
(\(j \neq j_i\)) only and are NA in the proband.
c_star_hat: Family-level chi-square goodness of fit statistic,
\(\hat{c}^{*}_{i}\). The same value is provided for each family
member.
c_star_hat_df: Degrees of freedom for \(\hat{c}^{*}_{i}\), which
is equal to the number of non-probands in the family. The same value
is provided for each family member.
p_c_star_hat: Probability of obtaining a deviate as or more extreme
than \(\hat{c}^{*}_{i}\), \(\hat{p}_{\hat{c}^{*}_{i}}\). The
same value is provided for each family member.
r_star_hat: Individual-level goodness of fit statistic,
\(\hat{r}^{*}_{ij}\). These are defined for family members
(\(j \neq j_i\)) only and are NA in the proband.
get_objfun()Returns TMB::MakeADFun() object used to construct the
instance.
FamLMMFit$get_objfun()
get_objfun_par_names()Returns a vector of names derived from the original formula
that map to each element of objfun$par.
FamLMMFit$get_objfun_par_names()
print()Prints contents of FamLMMFit objects with nice formatting.
FamLMMFit$print(...)
...Arguments passed on to print_ests().
get_h2_a_lrts()Perform likelihood ratio test(s) for no polygenic effect(s)
FamLMMFit$get_h2_a_lrts(print = TRUE, use_cached = TRUE, ...)
printIf TRUE (default), prints the likelihood ratio test
results in a nice format.
use_cachedIf TRUE (default), use cached likelihood ratio
test results if any exist. Otherwise, new likelihood ratio tests will
be run, and these results will replace any in the cache.
...Additional parameters to pass to the control list for
optim() with method = "L-BGFS-B". Note that parscale and
fnscale cannot be modified.
Tests that each narrow-sense heritability parameter is zero
individually using a likelihood ratio test. See
vignette("linear_mixed_models") for a detailed description of the
methods used. By default, results are cached in the FamLMMFit
object after the first call to avoid redundant optimizations on
subsequent calls.
A data.table containing likelihood ratio test results,
invisibly.
clone()The objects of this class are cloneable with this method.
FamLMMFit$clone(deep = FALSE)
deepWhether to make a deep clone.