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Merge pull request #216 from sfcheung/devel
Finalize to 0.2.8
2 parents 0484a46 + 99d7b14 commit f7a48f8

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‎DESCRIPTION

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Package: manymome
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Title: Mediation, Moderation and Moderated-Mediation After Model Fitting
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Version: 0.2.7.1
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Version: 0.2.8
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Authors@R:
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c(person(given = "Shu Fai",
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family = "Cheung",
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rmarkdown,
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semPlot,
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semptools,
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semTools,
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lavaan.mi,
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Amelia,
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mice,
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testthat (>= 3.0.0)

‎NEWS.md

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# manymome 0.2.7.1
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# manymome 0.2.8
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## New Features
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- Updated to use `lavaan.mi` instead of
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`semTools`. (0.2.7.2, 0.2.7.3)
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## Miscellaneous
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- Added the option to disable the
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computation of implied statistics
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in `do_boot()` and `do_mc()`. This
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only by developers and advanced users.
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(0.2.7.1)
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- Moved `compute_implied_stats` to the
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end of the argument list to avoid
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conflicting with calls that do not
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name the arguments. (0.2.7.4)
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- Revised `mod_levels()` to prepare
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for latent variable moderation.
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(0.2.7.5)
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# manymome 0.2.7
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## New Features

‎R/boot2est_lavaan.R

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@@ -182,11 +182,11 @@ fit2boot_out <- function(fit,
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fit2boot_out_do_boot <- function(fit,
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R = 100,
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seed = NULL,
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compute_implied_stats = TRUE,
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parallel = FALSE,
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ncores = max(parallel::detectCores(logical = FALSE) - 1, 1),
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make_cluster_args = list(),
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progress = TRUE,
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compute_implied_stats = TRUE,
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internal = list()) {
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if (identical(internal$gen_boot, "update")) {
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environment(gen_boot_i_update) <- parent.frame()

‎R/boot2est_lm.R

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#'
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lm2boot_out <- function(outputs, R = 100,
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compute_implied_stats = TRUE,
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seed = NULL,
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progress = TRUE) {
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progress = TRUE,
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compute_implied_stats = TRUE) {
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if (!missing(outputs)) {
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outputs <- auto_lm2list(outputs)
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}
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lm2boot_out_parallel <- function(outputs,
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R = 100,
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seed = NULL,
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compute_implied_stats = TRUE,
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parallel = FALSE,
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ncores = max(parallel::detectCores(logical = FALSE) - 1, 1),
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make_cluster_args = list(),
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progress = TRUE) {
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progress = TRUE,
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compute_implied_stats = TRUE) {
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if (!missing(outputs)) {
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outputs <- auto_lm2list(outputs)
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}

‎R/check_path.R

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#' It also support
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#' `lavaan.mi` objects
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' For example, in the following model
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#' in `lavaan` syntax
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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#' If it is a single model fitted by
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#' [lm()], it will be automatically converted
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#' to a list by [lm2list()].

‎R/cond_indirect.R

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#' effects, indirect effects, or
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#' conditional indirect effects in a
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#' structural model fitted by [lm()],
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#' [lavaan::sem()], or [semTools::sem.mi()].
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#' [lavaan::sem()], or [lavaan.mi::sem.mi()].
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#'
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#' @details
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#'
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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#' If it is a single model fitted by
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#' [lm()], it will be automatically converted
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#' to a list by [lm2list()].

‎R/do_boot.R

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do_boot <- function(fit,
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R = 100,
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compute_implied_stats = TRUE,
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seed = NULL,
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parallel = TRUE,
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ncores = max(parallel::detectCores(logical = FALSE) - 1, 1),
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make_cluster_args = list(),
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progress = TRUE) {
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progress = TRUE,
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compute_implied_stats = TRUE) {
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if (!missing(fit)) {
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fit <- auto_lm2list(fit)
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}

‎R/do_mc.R

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#'
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#' It also supports a model estimated
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#' by multiple imputation using
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#' [semTools::runMI()] or its wrapper,
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#' such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or its wrapper,
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#' such as [lavaan.mi::sem.mi()].
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#' The pooled estimates and their
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#' variance-covariance matrix will be used
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#' to generate the Monte Carlo estimates.
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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#' The output of
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#' [stats::lm()] is not supported.
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#'
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do_mc <- function(fit,
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R = 100,
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compute_implied_stats = TRUE,
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seed = NULL,
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parallel = TRUE,
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ncores = max(parallel::detectCores(logical = FALSE) - 1, 1),
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make_cluster_args = list(),
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progress = TRUE) {
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progress = TRUE,
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compute_implied_stats = TRUE) {
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if (!missing(fit)) {
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fit <- auto_lm2list(fit)
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}

‎R/get_b.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param est The output of
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#' [lavaan::parameterEstimates()]. If

‎R/get_intercept.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param est The output of
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#' [lavaan::parameterEstimates()]. If

‎R/get_prod.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param est The output of
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#' [lavaan::parameterEstimates()]. If

‎R/index_mome.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param boot_ci Logical. Whether
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#' bootstrap confidence interval will be

‎R/indirect.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param est The output of
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#' [lavaan::parameterEstimates()]. If

‎R/indirect_proportion.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#'
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#' @references

‎R/lav_data_used.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param drop_colon Logical. Whether
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#' product terms (of the form "x:y")

‎R/lavaan_helpers.R

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group_number = NULL) {
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est0 <- methods::getMethod("coef",
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signature = "lavaan.mi",
53-
where = asNamespace("semTools"))(fit)
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where = asNamespace("lavaan.mi"))(fit)
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out <- get_implied_i_lavaan_mi(est0 = est0,
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fit = fit)
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out
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9090
get_vcov_lavaan_mi <- function(object) {
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methods::getMethod("vcov",
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signature = "lavaan.mi",
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where = asNamespace("semTools"))(object,
93+
where = asNamespace("lavaan.mi"))(object,
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type = "pooled",
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scale.W = TRUE,
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omit.imps = c("no.conv", "no.se"))
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139139
...,
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est_df = NULL) {
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if (is.null(est_df)) {
142-
est_df <- methods::getMethod("summary",
143-
signature = "lavaan.mi",
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where = asNamespace("semTools"))(fit,
145-
output = "data.frame",
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...)
142+
est_df <- lavaan.mi::parameterEstimates.mi(fit)
147143
}
148144
ptable <- as.data.frame(fit@ParTable)
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if (!is.null(ptable$est)) {
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187183
out <- lavaan::parameterTable(fit)
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coef_mi <- methods::getMethod("coef",
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signature = "lavaan.mi",
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where = asNamespace("semTools"))(fit)
186+
where = asNamespace("lavaan.mi"))(fit)
191187
se_mi <- sqrt(diag(get_vcov(fit)))
192188
id_free <- out$free > 0
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out$est <- NA

‎R/mc2est_lavaan.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
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#' its wrapper, such as [lavaan.mi::sem.mi()].
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#'
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#' @param compute_implied_stats If
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#' `TRUE`, default, implied statistics
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101101
#' @export
102102

103103
fit2mc_out <- function(fit,
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compute_implied_stats = TRUE,
105-
progress = TRUE) {
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progress = TRUE,
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compute_implied_stats = TRUE) {
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if (progress) {
107107
cat("Stage 1: Simulate estimates\n")
108108
}

‎R/mod_levels.R

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#' It can also be
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#' a `lavaan.mi` object
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#' returned by
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#' [semTools::runMI()] or
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#' its wrapper, such as [semTools::sem.mi()].
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#' [lavaan.mi::lavaan.mi()] or
58+
#' its wrapper, such as [lavaan.mi::sem.mi()].
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#' If it is a single model fitted by
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#' [lm()], it will be automatically converted
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#' to a list by [lm2list()].
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394394
rownames(out) <- vnames
395395
colnames(out) <- w
396396
}
397-
w_dat <- mm[, w]
397+
if (w_method %in% c("sd", "percentile")) {
398+
w_dat <- mm[, w]
399+
}
398400
if (w_method == "sd") {
399401
w_mean <- mean(w_dat, na.rm = TRUE)
400402
w_sd <- stats::sd(w_dat, na.rm = TRUE)

‎R/pseudo_jn.r

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#'
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#' This function supports models fitted
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#' by [lm()], [lavaan::sem()],
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#' and [semTools::sem.mi()]. This function
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#' and [lavaan.mi::sem.mi()]. This function
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#' also supports both bootstrapping
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#' and Monte Carlo confidence intervals.
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#' It also supports conditional

‎README.md

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[![R-CMD-check](https://github.com/sfcheung/manymome/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/sfcheung/manymome/actions/workflows/R-CMD-check.yaml)
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<!-- badges: end -->
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(Version 0.2.7.1, updated on 2025-02-22, [release history](https://sfcheung.github.io/manymome/news/index.html))
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(Version 0.2.8, updated on 2025-05-03, [release history](https://sfcheung.github.io/manymome/news/index.html))
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# manymome <img src="man/figures/logo.png" align="right" height="150" />
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@@ -97,9 +97,12 @@ by multiple regression. The package was introduced in:
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Supports datasets with missing data
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through `lavaan::sem()` with full information maximum likelihood (`fiml`).
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100-
In version 0.1.9.8 or later, it also supports missing data handled
101-
by multiple imputation if the models are fitted by `semTools::sem.mi()`
102-
or `semTools::runMI()` (see `vignette("do_mc_lavaan_mi")`).
100+
In version 0.2.7.3 or later, it also supports missing data handled
101+
by multiple imputation if the models are fitted by `lavaan.mi::sem.mi()`
102+
or `lavaan.mi::lavaan.mi()` (see `vignette("do_mc_lavaan_mi")`).
103+
(Support for `semTools::runMI()` and its wrappers was removed in
104+
version 0.2.7.3 because this and related functions were deprecated
105+
in `semTools`.)
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104107
- **Supports Numeric and Categorical Moderators**
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‎data-raw/test_mi_data.R

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#' #Create MI datasets for testing
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33
suppressMessages(library(lavaan))
4-
suppressMessages(library(semTools))
4+
suppressMessages(library(lavaan.mi))
55
suppressMessages(library(Amelia))
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# Categorical IVs in lavaan

‎inst/extdata/mi_test_data.RData

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