semTools 0.5-3 (in development)

New Functions:

• New discriminantValidity() function added.
• Support functions for the emmeans package (see ?lavaan2emmeans for examples)

New Features:

• class?lavaan.mi methods and functions can optionally specify particular imputation numbers to omit, in addition to the general omission criteria in omit.imps=. Simply include specific imputation numbers in the omit.imps= vector.
• Latent-interaction functions (e.g., probe2WayMC()) now work for lavaan.mi objects. The ?indProd documentation now includes an example adding product indicators to multiple imputed data sets.
• The update() method for class?measEq.syntax has a new argument change.syntax. Users can pass lavaan syntax specifying an existing model parameter in order to change the labels or the fixed/free values. This provies some flexibility not found in the measEq.syntax() function itself (e.g., releasing an equality constraint in only one of >2 groups, whereas group.partial= can only release constraints across all groups).
  • https://github.com/simsem/semTools/issues/60
• The as.character() method for class?measEq.syntax now accepts the argument package = "mplus", which prints the syntax as an Mplus MODEL command. The as.character() method also has 2 new arguments:
  • groups.as.blocks=TRUE optionally prints multigroup syntax in “block” format, which enables users to hack measEq.syntax() to specify multilevel CFA models with invariance constraints.
  • params= allows users to select specific types of parameters to print, making it easier to check particular aspects of the model specification (e.g., params = c("loadings","lv.variances") in metric invariance models).
• net() now accepts models fitted to categorical outcomes.
• reliability() includes 2 new arguments:
  • default dropSingle = TRUE is consistent with old behavior.
  • “total” column no longer returned by default, or ever for 1-factor models. Users can request return.total = TRUE when multiple factors are multiple dimensions of a single scale composite.
• New small-N corrections added to chisqSmallN() function. Also accepts lavaan.mi objects now.
• efaUnrotate() now accepts summary statistics when data=NULL.

Bug Fixes:

• reliability() and maximalRelia() returned an error with categorical single-group models
  • https://groups.google.com/d/msg/lavaan/rPVEHUQjqVQ/SQaMrgn-AQAJ
• reliability() only ignored higher-order factors without any observed indicators, and returned an error when first-order factors had categorical indicators. Both issues have been resolved:
  • https://github.com/simsem/semTools/issues/65
• fitMeasures() for lavaan.mi sometimes returned an error

semTools 0.5-2 (on CRAN 30 August 2019)

• Requires lavaan version 0.6-5

• Minor bug fixes

• Addition of the plausibleValues() function to extract plausible values (i.e., multiple imputations) of factor scores from objects of class lavaan, lavaan.mi, or blavaan

• Full support for lavaan.mi models fitted to multiply imputed multilevel data; resolved issue (#39).

• Full support for fixed.x=TRUE and conditional.x=TRUE in lavaan.mi models, including std.nox solutions in summary(), modindices.mi(), and lavTestScore.mi().

• Added the omit.imps= argument to all lavaan.mi-related functions, optionally excluding solutions that did not converge, failed to estimate SEs, or contained NPD matrices (Heywood cases are a special case). Only the first 2 are excluded by default.

• reliability(), reliabilityL2(), and maximalRelia() now accept lavaan.mi objects

• Added (S)EPCs to lavTestScore.mi() output when epc=TRUE

• Added (A)RIV/FMI to all pooled tests when available for lavaan.mi objects, to quantify additional uncertaintly in the test statistic due to missing data.

• Allow multigroup models in plotProbe() and related latent-interaction functions.

• standardizeMx() was deprecated in previous versions, now removed.

semTools 0.5-1 (on CRAN 25 September 2018)

• Requires lavaan version 0.6-3

• Minor bug fixes

• The formerly deprecated lisrel2lavaan() function has been removed from semTools

• compareFit() now accepts lavaan.mi objects returned by runMI()

• For lavaan.mi objects returned by runMI(), the anova() method has been updated to behave more like lavaan’s anova() method:

  • more than 2 nested models can be compared
  • fit indices are no longer an option, and must be requested using the fitMeasures() method

• Given the previous addition of score-test functions modIndices.mi() and lavTestScore.mi() for lavaan.mi objects (parallel to modIndices() and lavTestScore() for lavaan objects), the remaining “trilogy” of tests in lavaan (lavTestLRT() and lavTestWald()) now have parallel functions for lavaan.mi objects: lavTestLRT.mi() and lavTestWald.mi()

  • lavTestWald.mi() implements what was formerly available in using anova(..., test = "D1")
  • lavTestLRT.mi() implements what was formerly available in using anova(..., test = "D3")
  • lavTestLRT.mi() cannot compare more than 2 nested models. The anova() method internally calls the compareFit() function to compare multiple lavaan.mi objects.
  • For all 3 tests (score, Wald, and LRT), the “D2” pooling method is an option, and there is a newly public function calculate.D2() that can be used to pool any set of Wald chi-squared or z statistics.

• The runMI() function can now be applied to multilevel SEMs that can be fitted with lavaan()

  • Known issue (#39): fitted() and resid() methods will not yet work in models with both multiple levels and multiple groups. This will be resolved in a future version.

• The 3 functions measurementInvariance(), measurementInvarianceCat(), and longInvariance() have been deprecated, redirecting users to the new measEq.syntax() function. It is much more general, capable of combining features of all 3 deprecated functions without their restrictions.

  • The function’s primary purpose is writing syntax that users can read and edit.
  • The fitting of a model is optional, and fitting multiple models is not (yet) automated. See the ?measEq.syntax help-page examples for how to fit and compare several levels of invariance.
  • Find many more details posted on the lavaan forum (the Google group).

semTools 0.5-0 (on CRAN 1 July 2018)

• Requires lavaan version 0.6-1

• Minor bugs fixed

• Minor convenience features added

• Redesigned runMI() function, which no longer produces an object of class lavaanStar (that object class is no longer supported), which inherited from class lavaan. It now produces an object of class lavaan.mi, which inherits from lavaan’s new lavaanList class (see the ?lavaanList help page for details). The reasons to redesign runMI() include:

  • The user was required to choose among available methods for pooling the chi-squared test statistic when fitting the model, and the baseline model was also fit so that incremental fit indices (e.g., CFI and TLI) could be calculated. This lead to more frequent convergence problems.
  • The lavaanStar class could inadvertently mislead users into thinking that certain results were available from multiple imputations that were not. For example, the modindices() function would return modification indices for the first imputation, but those were not appropriately pooled statistics.

• The new runMI() no longer includes the chi= argument, because those options have been moved to an anova() method written for lavaan.mi objects. Additional methods have been written: see the class?lavaan.mi help page for a list of methods and details about their use. Additionally, appropriately pooled modification indices and (S)EPCs are now available for multiple imputations (via modindices.mi()), as well as a general score test via lavTestScore.mi().

• The parcelAllocation() has also been redesigned with new arguments to improve its flexibility and ease of use. Users are now required to provide lavaan syntax not only for the parcel-level model, but also for the item-level model. This allows parcel allocation to be automatically detected, no longer requiring users to provide a list of item-to-parcel assignments (see new examples on the help page).

• The OpenMx enhancements in previous versions of semTools are obsolete now that OpenMx provides fit indices and standardized paths, so they have been removed. However, standardizeMx() is still available (temporarily deprecated) to provide standardized mean-structure parameters, until the OpenMx maintainers add that feature to OpenMx::mxStandardizeRAMpaths().

• measurementInvariance() and measurementInvarianceCat() now require users to name all arguments passed to cfa(), including the first argument: model=. This is to prevent errors that occurred when some previous users had passed arguments in a different order than expected, which should not be a limitation.

semTools versions < 0.5

Find our remaining version history on GitHub:

https://github.com/simsem/semTools/wiki/Version-History