Summary and print methods for results from HLfit or related functions. summary
may also be used as an extractor (see e.g. beta_table
).
# S3 method for HLfit
summary(object, details=FALSE, max.print=100L, verbose=TRUE, ...)
# S3 method for HLfitlist
summary(object, ...)
# S3 method for fixedLRT
summary(object, verbose=TRUE, ...)
# S3 method for HLfit
print(x,...)
# S3 method for HLfitlist
print(x,...)
# S3 method for fixedLRT
print(x,...)
The return object of HLfit or related functions.
The return object of HLfit or related functions.
For summary.HLfit
, whether to print the screen output that is the primary purpose of summary. verbose=FALSE
may be convenient when summary
is used as an extractor. For summary.fixedLRT
, whether to print the model fits or not.
Controls options("max.print")
locally.
A vector with elements controlling whether to print some obscure details. Element ranCoefs=TRUE
will print details about random-coefficients terms (see Details); and element p_value="Wald"
will print a p-value for the t-value of each fixed-effect coefficient, assuming a gaussian distribution of the test statistic.
further arguments passed to or from other methods.
These methods return the object invisibly. They print details of the (lower level) HLfit results in a convenient form.
The random effect terms of the linear predictor are of the form ZLv. In particular, for random-coefficients models (i.e., including random-effect terms such as (z|group)
specifying a random-slope component), correlated random effects are represented as b = Lv for some matrix L, and where the elements of v are uncorrelated. In the output of the fit, the Var.
column gives the
variances of the correlated effects, b=Lv. The Corr.
column(s) give their correlation(s). If details
is TRUE, estimates and SEs of the (log) variances of the elements of v are reported as for other random effects in the Estimate
and cond.SE.
columns of the table of lambda coefficients. However, this non-default output is potentially misleading as the elements of v cannot generally be assigned to specific terms (such as intercept and slope) of the random-effect formula, and the representation of b as Lv is not unique.
# NOT RUN {
## see examples of corrHLfit usage
# }
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