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reghelper 1.1.1

  • Fixes bug with very long lists of variables in build_model() or cell_means()
  • Properly throws error for graph_model() when required inputs are not specified
  • Fixes bug with beta() for glm models that include an offset value
  • Fixes bug with simple_slopes() when one variable name is a subset of another variable name
  • Fixes bug with simple_slopes() when default contrast options are changed

reghelper 1.1.0

  • Adds David Beiner as a co-maintainer of the package
  • Support for confidence intervals for simple_slopes()

BUG FIX

  • Fixes warning raised when using a long formula with simple_slopes()

reghelper 1.0.2

BUG FIXES

  • Fixes errors in beta() and simple_slopes() resulting from factor variables that have spaces or other special characters
  • Adds support for character vectors added to models, where R silently converts them to factors
  • Fixes error in graph_model() documentation

reghelper 1.0.1

BUG FIX

  • Fixes error raised when weights were used in lm and lme4 models. This occurred in several functions, including beta(), simple_slopes(), and sig_regions(). Weights should now properly be applied without issue.

reghelper 1.0.0

Just a note: While reghelper has officially reached version 1.0.0, the fact is that it has been stable and relatively feature complete quite some time. The change from v0.3.6 to v1.0.0 is not drastic, but does involve some minor breaking changes, hence an increase to the major version number. But quite frankly, it should have been bumped to v1.x a long time ago.

BREAKING CHANGES

  • The beta() method has now been removed for nlme and lme4 models. These had been deprecated in the previous release. See the README for more details: https://github.com/jeff-hughes/reghelper
  • Minor breaking changes. These should not impact most users, but could impact those who are extracting elements from the output of these functions in a programmatic fashion:
    • simple_slopes() for an lme4 model now returns a data frame of class simple_slopes rather than simple_slopes_lme4
    • When running simple_slopes() with categorical variables with more than two levels (i.e. a factor variable with two or more contrasts), the output now provides the name of the contrast in the parentheses after the sstest label. Users who are extracting values should use startsWith(value, 'sstest') rather than value == 'sstest' to match appropriately.

BUG FIXES

  • Fixes issues with incorrect variable labels in simple_slopes() output when there is more than one categorical variable with more than two levels.
  • Provides better support for lmerTest models in simple_slopes()

reghelper 0.3.6

This release deprecates the beta() method for nlme and lme4 models. See the README for more details: https://github.com/jeff-hughes/reghelper

reghelper 0.3.5

This is a patch release to fix a bug in the beta() function, to allow use of lmerTest models.

reghelper 0.3.4

This is a patch release to cover changes made to the ggplot2 package.

BUG FIXES

  • Fixed simple_slopes() to cover cases of contrasts that have no column names.

reghelper 0.3.3

This is a patch release covering changes necessary to prepare for submission to CRAN. Most changes will not affect current code; however, be aware of the following changes:

  • Many of the functions have had the dots parameter (…) added, to ensure consistency with the S3 generic function. However, any extra parameters will simply be ignored. Thus, this does not impact any user code.

  • Package functions which implement the following generic methods have had their first parameter renamed, again for consistency with the S3 generic: summary, print, coef, residuals, fitted. In most cases, this will not impact user code, unless you have used named parameters, e.g., summary(model=results) should now be summary(object=results).

BUG FIXES

  • Fixed bug when using build_model but only providing a single model to be run.

  • Created special print method for simple_slopes so that “lme4” models print correctly.

  • Fixed bug (correctly this time) with simple_slopes using incorrect contrasts for factor variables.

reghelper 0.3.2

BUG FIXES

  • Fixed bug with simple_slopes using incorrect contrasts for factor variables. Resolves Issue #2.

reghelper 0.3.1

  • build_model now drops missing data based on the variables included in the final model, so that all models are tested on the same data.

  • The titles parameter of graph_model has been changed to labels, and now takes a named list rather than relying on the index of a character vector.

  • graph_model function extended to include lme and merMod models.

reghelper 0.3.0

NEW FEATURES

  • beta function extended to include lme and merMod models.

  • build_model function extended to include aov and glm models.

  • cell_means function extended to include glm models.

  • graph_model function extended to include aov and glm models.

  • sig_regions function extended to include glm models.

reghelper 0.2.0

MAJOR CHANGES

  • Changed block_lm function name to build_model.

NEW FEATURES

  • Added examples to documentation for all functions.

  • beta function extended to include glm models.

  • cell_means function extended to include aov models.

  • ICC function extended to include merMod models (from “lme4” package).

  • simple_slopes function extended to include aov, glm, lme, and merMod models.

  • simple_slopes now includes print function to include significance stars.

BUG FIXES

  • Fixed bug with passing variables names to build_model, cell_means, and graph_model. Resolves Issue #1.

reghelper 0.1.0

NEW FEATURES

  • beta function calculates standardized beta coefficients.

  • block_lm function allows variables to be added to a series of regression models sequentially (similar to SPSS).

  • ICC function calculates the intra-class correlation for a multi-level model (lme only at this point).

  • cell_means function calculates the estimated means for a fitted model.

  • graph_model function graphs interactions at +/- 1 SD (uses ggplot2 package).

  • simple_slopes function calculates the simple effects of an interaction.

  • sig_regions function calculate the Johnson-Neyman regions of significance for an interaction.