cbcTools (development version)

cbcTools 0.7.1

• Auto-encoding to dummy coding occurs for cbc_choices and cbc_power if the design is detected to have a no_choice option.
• Updated some of the print methods so that they don’t error if the choices or design objects are modified by dplyr functions.

cbcTools 0.7.0

• Re-configures the design encoding to use “standard” coding by default.
• Reasoning for standard coding by default is for easier interpretation of summary metrics like balance and overlap.
• New function cbc_encode() used to convert designs to dummy or effects coding.

cbcTools 0.6.4

• Adds balance_by argument to force balanced sampling in designs with restricted or otherwise unbalanced levels across attributes.
• Fixes issue where remove_dominant was not working if there was a no_choice option.

cbcTools 0.6.3

• Improve the greedy methods to include proper handling of the dominance checking and overall efficiency improvements.

cbcTools 0.6.1

• Added include_probs argument to cbc_design(), which includes predicted choice probabilities in the returned design data frame if include_probs = TRUE. Defaults to FALSE.

cbcTools 0.6.0

• Major overhaul of the package with breaking changes.
• New function, `cbc_priors()``. This allows users to specify a set of priors according to a wide variety of model specifications, including random parameters (with or without correlated heterogeneity), interactions, and “no choice” options. These priors can then be used to create designs and simulate choices.
• Coefficients for levels of an attribute in cbc_priors() can be named vectors, addressing #24.
• Major overhaul of the cbc_design() function, with entirely new algorithms for searching for designs
  • One is “random”, three are frequency-based (“greedy”) algorithms, and three more are d-error minimizing algorithms.
  • Old methods removed: "full", "orthogonal", "dopt", "CEA", and "Modfed"
  • Bayesian D-efficient designs are now created based on the priors provided. With random parameters in the priors, a Bayesian D-efficient design will be created.
  • New support for removing dominant alternatives from designs.
  • New support for randomizing the order of questions and alternatives across respondents, addresses #29.
  • New cbc_inspect() function for comprehensively inspecting designs.
  • New cbc_compare() function for comparing designs.
  • New functionality in cbc_power() for computing visualizing power analyses.

cbcTools 0.5.2

• Bug fix in checking input settings (#34)

cbcTools 0.5.1

• Patch to fix a joining issue in the join_profiles() function (#27)

cbcTools 0.5.0

• Further revisions to the method argument in the cbc_design() function.
• Added the "random" and "dopt" methods.
• Added restrictions so that orthogonal designs cannot use the label argument or restricted profile sets (as either of these would result in a non-orthogonal design).

cbcTools 0.4.0

• Adjustments made to the method argument in the cbc_design() function in preparation for potentially adding new design methods.
• Added the "orthogonal" option for generating orthogonal designs.

cbcTools 0.3.4

• Another small bug fix in cbc_design() related to #16 where factor level ordering for categorical variables were being mis-ordered.
• Updated how the method argument is handled by default in cbc_design() to be more flexible (anticipating other methods in the future).
• Added keep_db_error arg to cbc_design().

cbcTools 0.3.3

• Bug fix in cbc_design() where factor level ordering for categorical variables were being mis-ordered.
• Added additional input check for appropriate priors in cbc_design().

cbcTools 0.3.2

• Modify how restrictions are defined in the cbc_restrict() function to allow users to provide expressions.

cbcTools 0.3.1

• Add cbc_restrict() function to improve UI for adding restrictions to profiles.
• Remove previous approach to including restrictions in cbc_profiles().
• Add new test cases

cbcTools 0.3.0

• Bug fix: modify code in cbc_design() to avoid duplicate choice sets for the same respondents; addresses #7.
• Bug fix: modify code in cbc_design() to allow Bayesian D-efficient designs with restricted profile sets; addresses #10 and #9.

cbcTools 0.2.0

• Added a startup message when the package is loaded.
• Updates for compatibility with logitr version 1.0.1.
• Updated DESCRIPTION and CITATION to remove redundancy in title.
• Updated documentation of returned values in several functions.

cbcTools 0.1.0

• Added initial integration with {idefix} packages for Bayesian D-efficient designs

cbcTools 0.0.5

• Updates for compatibility with logitr version 0.8.0.

cbcTools 0.0.4

• Updates for compatibility with logitr version 0.7.0.

cbcTools 0.0.3

• Modified the argument of cbc_profiles() to ... so that the user no longer needs to create a separate list to define the attributes and levels.
• Modified the arguments for the randN() and randLN() functions to mean and sd.
• Improved printing of counts in cbc_balance() and cbc_overlap().
• Updated names of random parameter models to match that of future logitr v0.6.0.
• Updated documentation and examples for all functions.
• Adding piping example to readme.

cbcTools 0.0.2

• Added support for conditional levels in cbc_profiles()

cbcTools 0.0.1

• Added a NEWS.md file to track changes to the package.