# manymome 0.3.6

## New Features

- Updated the `q_*` functions
  (`q_mediation()`, `q_simple_mediation()`,
  `q_serial_mediation()` and `q_parallel_mediation()`)
  to support fitting a model on scale
  scores computed using user-supplied
  list of indicators if `indicator_method`
  is set to `"scale_scores"`. If
  `indicator_method` is set to
  `measurement_model` and the fit method
  is structural equation modeling, then
  a latent variable model with
  a measurement part will be fitted.
  (0.3.4.2, 0.3.4.3, 0.3.4.22)

- Added preliminary support for SAM
  to the `q_*` functions
  (`q_mediation()`, `q_simple_mediation()`,
  `q_serial_mediation()` and `q_parallel_mediation()`).
  (0.3.4.9)

- Preliminary support for latent-variable
  moderation and moderated-mediation
  supported if a model is fitted by SAM.
  (0.3.4.14, 0.3.4.22, 0.3.4.23,
   0.3.4.24, 0.3.4.25)

## Miscellaneous

- The quick functions now properly handle
  a data frame which has already been processed
  by `na.omit()` and so has the attribute
  `na.action` set. (0.3.4.1)

- Updated `do_boot()` to handle a fit
  object with empty cases (cases included
  but not used due to missing data on
  all variables in the model).
  (0.3.4.5)

- Updated `do_boot()` to support the
  output of `lavaan::sam()`.
  (0.3.4.6)

- Fixed a message in the printout of
  `q_mediation()`.
  (0.3.4.10, 0.3.4.20)

- Updated `q_mediation()` to use
  `lavaan::standardizedSolution()`
  when `fixed.x = FALSE`.
  (0.3.4.11)

- Added `get_fit()` to retrieve the
  fit results (regression or SEM)
  stored in the output of `q_mediation()`
  and friends.
  (0.3.4.18)

# manymome 0.3.4

## Improvements

- The `plot`-method of `cond_indirect_effects`
  objects will keep the order of the
  moderator levels (from bottom to top)
  as appeared in the object.
  Set `keep_wlevels_order` to `FALSE` to
  revert to the old behavior. Default
  is `NULL`, and the order will be
  determined internally.
  (0.3.3.4, 0.3.4)

## Miscellaneous

- The argument `na.action` in
  `q_mediation()` and friends is no
  longer supported because it is
  unnecessary, and using it can be
  confusing. For `fit_method = "sem"`,
  we can just set `missing` to
  `"listwise"` to request
  listwise deletion. (0.3.3.1)

- Updated `lavaan.mi` test objects
  for `lavaan 0.6-21`. (0.3.3.2)

- No more warning (a false alarm) when
  some category names have one
  or more white spaces.
  (0.3.3.6)

## Bug Fixes

- Fixed the error message
  of `plot.cond_indirect_effects()`
  when a model has no latent
  variables but `x_method` is set to
  `"percentile"`. (0.3.3.3)

- The `print` method of the outputs of
  `q_mediation()` and friends now prints
  the total indirect effects for an
  arbitrary model. (0.3.3.5)

- Fixed a bug in `plot.cond_indirect_effects()`
  with `facet_grid_*` when the options
  `useFancyQuotes` is set to `TRUE`.
  (0.3.3.7)

# manymome 0.3.3

## Miscellaneous

- Updated some tests to tolerate minor
  differences due to optimization in
  OpenBLAS platforms. (0.3.2.1)

- Update the reference for `delta_med()`.
  (0.3.2.2)

# manymome 0.3.2

## Miscellaneous

- Added the `internal_options` argument to
  `cond_effect()` for adding advanced
  options in the future. For now, it
  can be used to set `pvalue_min_size`
  to override the default minimum number
  of bootstrap samples for computing
  asymmetric bootstrap *p*-value. Several
  other functions are also updated to
  work according to this argument.
  (0.3.1.1)

- Added `skip_ci` to `internal_options` to
  skip the computation of bootstrap
  and Monte Carlo CIs.
  For functions that only need the
  bootstrap or Monte Carlo estimates but
  not the CIs. (0.3.1.2, 0.3.1.3)

- Added Monte Carlo asymmetric *p*-values.
  They will not be printed for now. They
  are used by external functions that only
  need to test the null hypothesis.
  (0.3.1.3, 0.3.1.4)

- Update the internal test data created
  from `lavaan.mi` objects. (0.3.1.5)

# manymome 0.3.1

## New Features

- Updated the `q_*` functions
  (`q_mediation()`, `q_simple_mediation()`,
  `q_serial_mediation()` and `q_parallel_mediation()`)
  to support fitting a model by
  path analysis using `lavaan::sem()`,
  with the option to handle missing data
  using full information maximum likelihood.
  (0.2.9.3)

- Added a plot method for the output
  of `q_mediation()`
  and its friends. Requires `semptools`
  (0.3.2 or above), which needs to be
  installed separately.
  (0.2.9.4, 0.2.9.5, 0.2.9.6)

- Updated `q_mediation()` to support
  a user-specified mediation model.
  (0.2.9.3)

## Miscellaneous

- Improved the printout of a list of
  indirect effects. (0.2.9.1, 0.2.9.2)

- Added the `skip_indicators` argument to
  `get_prod()` and related functions
  for skipping observed indicators when
  identifying product terms. Set to
  `TRUE` by default. Models using the
  product-of-indicator approach is not
  supported anyway and so they can be
  skipped. (0.2.9.8)

## Bug Fixes

- Fixed the error raised when `do_mc()`
  is used for some multigroup models with
  latent variables. No impact on results
  because latent means are not
  used for now. (0.2.9.7)

# manymome 0.2.9

## Miscellaneous

- Optimized the speed of `do_mc()`.
  It now runs much faster than previous
  versions. (0.2.8.1, 0.2.8.2)

- Optimized the speed of `do_boot()`.
  It now runs faster than previous
  versions. (0.2.8.3)

- Removed `semTools` and `semptools`
  from `Suggests` because vignettes
  that use them are precomputed. They
  are not needed to generate the vignettes.

## Bug Fixes

- Fixed the error raised in some
  special cases when plotting a direct path
  with many product terms. (0.2.8.4)

# manymome 0.2.8

## New Features

- Updated to use `lavaan.mi` instead of
  `semTools`. (0.2.7.2, 0.2.7.3)

## Miscellaneous

- Added the option to disable the
  computation of implied statistics
  in `do_boot()` and `do_mc()`. This
  experimental feature allow faster
  computation of Monte Carlo estimates,
  and does not affect the computation of
  unstandardized effects. Should be used
  only by developers and advanced users.
  (0.2.7.1)

- Moved `compute_implied_stats` to the
  end of the argument list to avoid
  conflicting with calls that do not
  name the arguments. (0.2.7.4)

- Revised `mod_levels()` to prepare
  for latent variable moderation.
  (0.2.7.5)

# manymome 0.2.7

## New Features

- Added several "quick" functions for
  fitting regression models and testing
  indirect effects in one call:
  `q_simple_mediation()`,
  `q_serial_mediation()`, and
  `q_parallel_mediation()` for
  simple, serial, and parallel
  mediation models, respectively. Also
  added an article to the website to
  introduce these functions.
  (0.2.5.1, 0.2.5.2, 0.2.5.3, 0.2.5.4)

## Miscellaneous

- Updated the summary
  method of `lm_list`
  objects (`print.summary_lm_list()` and
  `summary.lm_list()`) for computing
  confidence intervals and proper
  standardized coefficients (only
  numerical variables standardized,
  and derived terms formed after
  standardization). They are disabled
  by default (`betaselect = FALSE` and
  `ci = FALSE`) for backward compatibility.
  (0.2.5.4)

- Made some examples faster to run to
  meet the CRAN requirement on examples.
  (0.2.7)

# manymome 0.2.5

## New Features

- Added the `as.data.frame` method
  (`as.data.frame.cond_indirect_effects()`)
  for `cond_indirect_effects` objects.
  The `print` method (`print.cond_indirect_effects()`)
  now calls this method internally. (0.2.4.4)

## Improvement

- Though rare in real studies,
  `merge_mod_levels()` was revised to
  support merging `wlevel` objects
  that have only one level in each of
  them. (0.2.4.1)

- When bootstrapping is done by `lavaan`,
  only bootstrap estimates with no
  errors will be kept (previously, they
  will be set to `NA`). This also makes
  the number of bootstrap samples reported
  consistent with the number of successful
  bootstrap replications. (0.2.4.2)

- For functions such as `cond_effects()`,
  if the model has only one outcome
  variable (e.g., moderation only and
  has no mediator), then the `y` argument
  can be omitted. (0.2.4.6)

## Bugs

- Remove a warning that may occur when
  retrieving `lavaan` bootstrap estimates.
  (0.2.4.2)

## Miscellaneous

- Corrected the help page of
  `indirect_effects_from_list()`. It
  works on an object of the class
  `indirect_list`, not of the class
  `cond_indirect_effects`. (0.2.4.3)

- Updated the vignettes (0.2.4.5).

- Updated the internal `lavaan.mi` objects
  used for tests. (0.2.4.7)

- Add `on.exit()` to ensure that the clusters
  created will be cleared if a function
  is aborted (e.g., terminated by users).
  (0.2.4.8)

- Updated the way the expected CPU time
  for bootstrapping, and the time is
  displayed only if `progress` is
  `FALSE`. (0.2.4.9)

# manymome 0.2.4

## New Features

- The `plot()` method of the output
  of `cond_indirect_effect()` now supports
  using `facet_grid()` to plot the
  conditional effects when there are
  two or more moderators in a path.
  (0.2.3.3, 0.2.3.5, 0.2.3.6, 0.2.3.13)

## Improvement

- If all paths have the same `x`
  variables, the argument `x` can be
  omitted when calling
  `total_indirect_effect()`. Similarly,
  if all paths have the same `y`
  variables, the argument `y` can also be
  omitted when calling
  `total_indirect_effect()`. (0.2.3.2)

- If appropriate, most functions will
  automatically convert a single
  model fitted by `lm()` to a list by
  `lm2list()`. This allows users to
  use the output of `lm()` directly,
  such as when computing effects in a
  moderation-only model. (0.2.3.4)

- *P*-values and confidence intervals
  based on standard errors will now be
  computed even for direct paths not
  moderated. (0.2.3.8)

- Added `print_all_cond_indirect_effects()`
  and `print_all_cond_effects()` for
  printing the full output of all
  conditional indirect effects.
  (0.2.3.9)

- Updated the `print` method of
  indirect effect to print *p*-value
  and confidence interval computed from
  original standard error when
  appropriate. (0.2.3.10)

- Added `for_each_path` argument to the
  `print`-method of `indirect_list`
  objects. Setting it to `TRUE` to print
  each path in the output of
  `many_indirect_effects()` individually.
  (0.2.3.12)

- Added `wrap_computation` to the argument
  of `print.indirect()` to wrap the printout
  of long computational formulas. Default
  set to `TRUE`.
  (0.2.3.14)

- Updated `plot_effect_vs_w()` to check
  whether a moderator is numeric.
  (0.2.3.15)

- Updated `print.cond_indirect_effects()`.
  Disabled the printing of the (only)
  component path when a path has no
  mediator. (0.2.3.16)

## Documentation and Notes

- Corrected `README` to remark that
  dichotomous `x`-variables are supported
  by most functions if coded as a
  numeric dummy variable. (0.2.3.7)

- Fix the wording in the printout
  of `lm_list` objects. (0.2.3.11)

## Bug Fixes

- Fixed an issue related to
  the internal function
  `merge_model_matrix()` in some special
  cases. (0.2.3.1)

# manymome 0.2.3

## New Features

- Added support for using model-based
  standard errors (and the covariances)
  of estimates to compute the standard
  errors, *p*-values, and confidence
  intervals for conditional effects.
  This should be used only for effects
  without mediators and with both `x`-
  and `y`-variables not standardized.
  The standard errors, *p*-values,
  and confidence intervals are printed
  by default when certain conditions
  are met. These statistics are for
  models fitted by multiple regression.
  They should be used with cautions for
  models fitted by structural equation
  modeling because the model may not be
  invariant to linear transformation of
  variables if some covariances involving
  the product terms are not freely
  estimated. (0.2.2.1)

- Updated `pseudo_johnson_neyman()` to
  support the SE-based test. The method
  is equivalent to the (true)
  Johnson-Neyman when SE-based test is
  used. Added `johnson_neyman()` as an
  alias to `pseudo_johnson_neyman()`.
  (0.2.2.4)

- Added `fill_wlevels()` to add levels
  of moderator to an output of
  `cond_indirect_effects()`, such that
  the confidence band of a plot of
  effects against a moderator can be
  smoother. (0.2.2.7)

## Bug Fixes

- Fixed some issues related to
  `mod_levels()` in some special
  cases. (0.2.2.5)

## Miscellaneous

- Fixed a minor typo in the example
  of `indirect_effect()`. (0.2.2.8)

- Added `cond_effects()`, an alias to
  `cond_indirect_effects()`. A better
  name when a path has no mediator.
  (0.2.2.9)

- Finalize 0.2.3. Kept only updates
  relevant to users of 0.2.2. (0.2.3)

# manymome 0.2.2

## New Features

- Added support for bias-corrected (BC)
  confidence intervals when bootstrapping
  is done. This can be requested by
  adding `boot_type = "bc"` in applicable
  funcion. BC confidence interval is
  not recommended in some recent works
  (see [Get Started](https://sfcheung.github.io/manymome/articles/manymome.html)
  for selected references). It is added
  merely for research purpose. (0.2.1.4)

## Miscellaneous

- Try not setting the environment when
  calling `gen_boot_i_lavaan()`, which
  may not be necessary. (0.2.1.2)

- Factored out confidence interval
  computation into an internal function.
  (0.2.1.3)

- `lm2list()` now supports having only
  one regression model as the input.
  This allows users to use functions
  such as `cond_indirect_effects()`
  on a model with only moderators.
  (0.2.1.5)

## Bug Fixes

- Fix a bug in `do_boot()` for
  multigroup models when all groups
  have exactly the same number of
  cases. (0.2.2.1)

# manymome 0.2.1

## 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](https://sfcheung.github.io/manymome/articles/med_mg.html)

    - 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 0.1.14.10,
      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()`. (0.1.14.7)

### 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()`. (0.1.14.14 - 0.1.14.15)

- 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.
   (0.1.14.16)

## Miscellaneous

- 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."
  (0.1.14.1)

- 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. (0.1.14.9,
  a bug fixed in 0.2.1)

# manymome 0.1.14

## 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. (0.1.13.2)

## Bug Fixes

- Fixed a nonessential bug with the math
  operator: `indirect_raw`, though not
  used for now, is now computed correctly
  when using `+` and `-`. (0.1.13.1)
- Fixed a minor typo in documentation.
  (0.1.13.3)
- Fixed a minor issue with the print
  method of `delta_med`-class object.
  (0.1.13.4)
- 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.
  (0.1.13.5)
- Fixed a few more tests that should
  not be run if suggested packages are
  not installed. (0.1.13.6)
- No longer raises an error for dichotomous
  moderators. (0.1.13.7)

# manymome 0.1.13

## New Features

- Added `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)
- Added support for paths with both
  latent and observed variables. (0.1.12.2, 0.1.12.4)

## Miscellaneous

- Updated references. (0.1.13)

# manymome 0.1.12

## 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. (0.1.11.2)

## Miscellaneous

- 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)

## Bug Fixes

- *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)

# manymome 0.1.10

## New Features

### Monte Carlo Confidence Intervals

- Added support for Monte Carlo confidence intervals. (0.1.9.3 to 0.1.9.4)
- Updated some vignettes for Monte Carlo confidence intervals. (0.1.9.5)
- Please refer to [this article](https://sfcheung.github.io/manymome/articles/do_mc.html)
  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. (0.1.9.8-0.1.9.10)
- Please refer to [this article](https://sfcheung.github.io/manymome/articles/do_mc_lavaan_mi.html)
  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. (0.1.9.7)

### Report proportion of effect mediated

- Added `indirect_proportion()` and two methods for its output. (0.1.9.12)

### Others

- Exported `get_prod()` and added [an article](https://sfcheung.github.io/manymome/articles/get_prod.html)
  on its workflow. (0.1.9.13).
- Bootstrapping can handle the `fixed.x` argument as `lavaan` does. (0.1.9.17)

## Bug Fixes

- Fixed `factor2var()` to work (again) for a categorical variable with only two
  levels. (0.1.9.21)

## Miscellaneous

- Updated badges in README.md. (0.1.9.1)
- Updated `pkgdown` site. (0.1.9.2)
- Used a more reliable test for Monte Carlo CIs. (0.1.9.6)
- Updated the logo for readability. (0.1.9.6)
- Fixed an error in `pkgdown` site. (0.1.9.6)
- Added progress bars to `do_mc()`. (0.1.9.11)
- Added `print.mc_out()`, the print-method for `mc_out`-class objects. (0.1.9.14)
- Updated vignettes with package name. (0.1.9.15)
- Fixed typos in NEWS.md. (0.1.9.15)
- Updated `pkgdown` GitHub action for using newer version of mermaid. (0.1.9.15)
- Updated `pkgdown` website to use the new logo and color scheme. (0.1.9.16)
- Modified more tests to accommodate a change in `lavaan`
  on handling random seed. (0.1.9.18)
- No change to the main code. Added a few technical appendices as `pkgdown`
  articles, accessible through the `pkgdown` website of the package. (0.1.9.19)
- Updated the documentation of functions to state that they support
  `lavaan.mi`-class objects. (0.1.9.20)

# manymome 0.1.9

## Miscellaneous

- 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

## New Features

### Bootstrapping

- Added `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)
- Added a print method for the output of `do_boot()`. (0.1.4.7)

### Mediation

- Added `all_indirect_paths()` for identifying all indirect paths
  in a model. (0.1.4.5)
- Added `many_indirect_effects()` for computing indirect
  effects for a list of paths. (0.1.4.5)
- Added `total_indirect_effect()` for computing the total
  indirect effect between two variables. (0.1.4.5)

## Bug Fixes

- Updated README.md with code for installing from CRAN. (0.1.4.1).
- Fixed a typo in README.md. (0.1.4.2)
- Fixed tests that should be done by `expect_equal` on numbers rather
  than on characters. No change in the functions. (0.1.4.3)
- Noted in the vignettes that some new functions are not
  yet on the CRAN version and available in the GitHub
  version. (0.1.4.6)
- Fixed a bug in `merge_model_frame()`. (0.1.4.8)

## Others

- Finalize Version 0.1.6 for CRAN.

# manymome 0.1.4.0

- Checked examples and vignettes to ensure
  parallel processing is not used. (0.1.3.1)
- Updated the DESCRIPTION (0.1.3.2)
- Release version for main. (0.1.4.0)

# manymome 0.1.3.0

- Release version for main. (0.1.2.0)
- Fixed an invalid link in Readme.md. (0.1.3.0)

# manymome 0.1.1.6

- Cleaned up the doc and code.

# manymome 0.1.1.5

- First public release.
