delta_med() for computing \(\Delta_{Med}\) (Delta_Med), an \(R^2\)-like measure of indirect effect
proposed by Liu, Yuan, and Li (2023). Can form nonparametric bootstrap
confidence interval for \(\Delta_{Med}\). (0.1.12.1, 0.1.12.3)se = TRUE). They are simply the standard
deviations of the bootstrap estimates (if bootstrap confidence intervals
are requested) or simulated estimates (if Monte Carlo confidence
intervals are requested). They should be interpreted with cautions
because the sampling distribution of the effect estimates may not be
symmetric. (0.1.11.2)Customized linters. (0.1.11.1)
Revised a test to accommodate a behavior of MKL when
MASS::mvrnorm() is used to generate pseudo random numbers.
(0.1.11.4)
Finalized to 0.1.12. (0.1.12)
P-value were not computed when mathematical operations
are conducted on effects using + and - before
version 0.1.11.2. This has been fixed. (0.1.11.2)
merge_model_matrix() failed if all variables in an
lm() output is already present in merged outputs. Fixed in
0.1.11.3. (0.1.11.3)
cond_indirect() did not hide the progress when Monte
Carlo CIs were requested and do_mc() was called internally.
Fixed. It now hides the progress if progress = TRUE.
(0.1.11.5)
runMI() or
sem.mi() from the semTools package using
multiple imputation. (0.1.9.8-0.1.9.10)indirect_proportion() and two methods for its
output. (0.1.9.12)get_prod() and added an
article on its workflow. (0.1.9.13).fixed.x argument as
lavaan does. (0.1.9.17)factor2var() to work (again) for a categorical
variable with only two levels. (0.1.9.21)pkgdown site. (0.1.9.2)pkgdown site. (0.1.9.6)do_mc(). (0.1.9.11)print.mc_out(), the print-method for
mc_out-class objects. (0.1.9.14)pkgdown GitHub action for using newer version
of mermaid. (0.1.9.15)pkgdown website to use the new logo and color
scheme. (0.1.9.16)lavaan
on handling random seed. (0.1.9.18)pkgdown articles, accessible through the
pkgdown website of the package. (0.1.9.19)lavaan.mi-class objects. (0.1.9.20)lavaan
on handling random seed.lm2boot_out_parallel() to do bootstrapping with
the output of lm() using parallel processing. This is the
default when do_boot() is used on the outputs of
lm(). (0.1.4.4)do_boot().
(0.1.4.7)all_indirect_paths() for identifying all indirect
paths in a model. (0.1.4.5)many_indirect_effects() for computing indirect
effects for a list of paths. (0.1.4.5)total_indirect_effect() for computing the total
indirect effect between two variables. (0.1.4.5)expect_equal on
numbers rather than on characters. No change in the functions.
(0.1.4.3)merge_model_frame(). (0.1.4.8)