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  • Try not setting the environment when calling gen_boot_i_lavaan(), which may not be necessary. (

Bug Fixes

  • Fix a bug in do_boot() for multigroup models when all groups have exactly the same number of cases. (

manymome 0.2.1

CRAN release: 2024-05-07

New Features

Multigroup Models Supported

  • Support for mediation paths in multigroup models fitted by lavaan has been added. Demonstrations can be found in this article

    • Many functions have been updated to work for multigroup models with mediators fitted by lavaan. Most common tasks support multigroup models. For functions that support moderators, the group variable will be used automatically as a moderator. Checks will be added to functions not yet support multigroup models to alert users.

    • For paths moderated in multigroup models, only some functions (e.g., cond_indirect_effect()) are supported. However, multigroup models with moderators are rare. Functions that do not yet support multigroup models (e.g, mod_levels()) will raise an error if used on a multigroup model. Support may be added in the future.

    • The + and - operators can now be used on different paths because they may be paths in different groups in multigroup models.

    • The plot-method of cond_indirect_effects-class objects will be forced to be a tumble graph if the lines for different groups are to be plotted. In these cases, the data within each group will be used, including standardization. This approach, though leading to results different from those in single-group model using the group as a moderator, makes more sense for multigroup models, in which the distribution of variables are allowed to be different between groups. Since, by default, the model implied statistics are used to determine the means and SDs used in drawing the plot. This approach is useful when between-group equality constraints are present.

    • The plot-method of cond_indirect_effects-class objects now supports plotting a path that involves latent variables. The model implied statistics will always be used for the latent variables when determining the means and SDs. This is useful because the group-variable can be treated as a moderator by cond_indirect_effects(). (

Other New Features

  • Added plot_effect_vs_w(). It can plot an effect (direct or indirect) against a moderator, using the output of cond_indirect_effects(). ( -

  • Added pseudo_johnson_neyman(). It used the pseudo Johnson-Neyman approach (Hayes, 2022) to find the value of a moderator at which the conditional effect (direct or indirect) changes from nonsignificant to significant (or vice versa), based on the confidence interval selected. (


  • If a dataset has a variable which is a product of itself and another variable (e.g., x*y == x), find_products() will be trapped in an infinite loop. This “product term” will no longer be treated as a “product term.” (

  • Bootstrapping and Monte Carlo simulation will no longer be run once for each path in many_indirect_effects(). If do_boot() or do_mc() is not used first but bootstrapping or Monte Carlo confidence intervals are requested, this process will be done only once, and the estimates will be reused by all paths. (, a bug fixed in 0.2.1)

manymome 0.1.14

CRAN release: 2024-02-16

New Features

  • The standardizers (scale_x and scale_y) for each bootstrap or simulated sample are now stored, such that the confidence interval of the unstandardized effect can be computed even if standardization is requested. (

Bug Fixes

  • Fixed a nonessential bug with the math operator: indirect_raw, though not used for now, is now computed correctly when using + and -. (
  • Fixed a minor typo in documentation. (
  • Fixed a minor issue with the print method of delta_med-class object. (
  • Fixed a bug with using do_mc() on a model which do not have a mean structure, has latent variables, and is estimated by multiple imputation. Error is no longer raised. (
  • Fixed a few more tests that should not be run if suggested packages are not installed. (
  • No longer raises an error for dichotomous moderators. (

manymome 0.1.13

CRAN release: 2023-10-06

New Features

  • Added delta_med() for computing ΔMed (Delta_Med), an R2-like measure of indirect effect proposed by Liu, Yuan, and Li (2023). Can form nonparametric bootstrap confidence interval for ΔMed. (,
  • Added support for paths with both latent and observed variables. (,


  • Updated references. (0.1.13)

manymome 0.1.12

CRAN release: 2023-08-21

New Features

Can report standard errors (if requested)

  • All major print methods of effects support printing standard errors (setting 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. (


  • Customized linters. (

  • Revised a test to accommodate a behavior of MKL when MASS::mvrnorm() is used to generate pseudo random numbers. (

  • Finalized to 0.1.12. (0.1.12)

Bug Fixes

  • P-value were not computed when mathematical operations are conducted on effects using + and - before version This has been fixed. (

  • merge_model_matrix() failed if all variables in an lm() output is already present in merged outputs. Fixed in (

  • 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. (

manymome 0.1.10

CRAN release: 2023-06-08

New Features

Monte Carlo Confidence Intervals

  • Added support for Monte Carlo confidence intervals. ( to
  • Updated some vignettes for Monte Carlo confidence intervals. (
  • Please refer to this article for an illustration on forming Monte Carlo confidence interval.

Multiple Imputation

  • Added support for models fitted by runMI() or sem.mi() from the semTools package using multiple imputation. (
  • Please refer to this article for an illustration on forming Monte Carlo confidence interval.

Can report p-value (if requested)

  • Some print methods support printing asymmetric bootstrap p-values using the method presented in Asparouhov and Muthén (2021) if bootstrapping confidence interval is requested. By default, p-values are not printed. (

Report proportion of effect mediated


  • Exported get_prod() and added an article on its workflow. (
  • Bootstrapping can handle the fixed.x argument as lavaan does. (

Bug Fixes

  • Fixed factor2var() to work (again) for a categorical variable with only two levels. (


  • Updated badges in (
  • Updated pkgdown site. (
  • Used a more reliable test for Monte Carlo CIs. (
  • Updated the logo for readability. (
  • Fixed an error in pkgdown site. (
  • Added progress bars to do_mc(). (
  • Added print.mc_out(), the print-method for mc_out-class objects. (
  • Updated vignettes with package name. (
  • Fixed typos in (
  • Updated pkgdown GitHub action for using newer version of mermaid. (
  • Updated pkgdown website to use the new logo and color scheme. (
  • Modified more tests to accommodate a change in lavaan on handling random seed. (
  • No change to the main code. Added a few technical appendices as pkgdown articles, accessible through the pkgdown website of the package. (
  • Updated the documentation of functions to state that they support lavaan.mi-class objects. (

manymome 0.1.9

CRAN release: 2023-01-06


  • Modified some tests to accommodate a change in lavaan on handling random seed.
  • Made some tests run faster to meet CRAN requirements.
  • Used precomputed results to speed up the building of vignettes.

manymome 0.1.6

CRAN release: 2022-11-06

New Features



Bug Fixes

  • Updated with code for installing from CRAN. (
  • Fixed a typo in (
  • Fixed tests that should be done by expect_equal on numbers rather than on characters. No change in the functions. (
  • Noted in the vignettes that some new functions are not yet on the CRAN version and available in the GitHub version. (
  • Fixed a bug in merge_model_frame(). (


  • Finalize Version 0.1.6 for CRAN.


CRAN release: 2022-09-06

  • Checked examples and vignettes to ensure parallel processing is not used. (
  • Updated the DESCRIPTION (
  • Release version for main. (


  • Release version for main. (
  • Fixed an invalid link in (


  • Cleaned up the doc and code.


  • First public release.