- General preparation for submitting package to CRAN.

- Added to
`nc_estimate_*`

function output the full model list as an attribute, that is really only necessary for those interested in the underlying models used for classifying the effects - Added a continuous outcome variable to simulated data that also links in with the DAG so that the linkage is more obvious (#97)
- Added function to create an edge table (#117)
- Incorporate tidyselect helpers into functions for selection of variables (#62)
- Added Getting Started vignette and an article on examples of using different models (#70)
- Added argument to
`nc_estimate_*_links()`

functions to set thresholds for classifying links (#157) - Added weights to be included to
`as_edge_tbl()`

(#142)

- Removed
`nc_classify_effects()`

and`nc_filter_estimates()`

, merged them into the two main estimation functions instead - Model summary statistics for
`lm`

and`glm`

models were removed for improving computing speed (they slowed things down quite a bit)

- Output all models used for classification as an attribute for the
`nc_estimate_*`

functions output - Use lavaan instead of dagitty to generate the simulated data
- Use standard GitHub Actions and remove AppVeyor
- Refactored some code within estimation method so it runs faster
- Tidied up the unit tests to run faster
- Removed duplicate or extra roxygen examples and instead referenced a common source with
`@seealso`

- Removed survival dependency
- Switch to using main instead of master branch

- For
`lm`

and`glm`

models, model summary statistics are added (#88). - Add a function to classify the direct effects between outcome or exposure and the network (#98).
- Add function to plot network graph:
`nc_plot_network()`

(#89, #110). - Added helper functions
`nc_adjacency_graph()`

,`nc_adjacency_matrix()`

, and`nc_partial_corr_matrix()`

to help create the weights for the network plot. (Issue #80, PR #89). - Removed soft deprecated functions. Using MuMIn over glmulti doesn’t change the results too much, see #60 for details (#83).
- Removed stringr dependency (#65, #83).

- Fix bug where too many digits caused a problem for
`pcor()`

(#125, #131). - Fix bug that didn’t properly filter variables nor identify neighbour nodes in
`nc_filter_estimates()`

(#109). - Fix problem with
`nc_standardize()`

that prevented the ability to use the`.regressed_on`

. argument to extract residuals (#108). - Input dataset can include missingness. Input data is treated as complete case for only the variables used in the modelling (#88).

- Rewrote underlying model estimation algorithm so it doesn’t use MuMIn and so there is one unified function for both outcome and exposure side estimation (#101)

- Add
`nc_standardize()`

function to standardize the metabolic variables (#73). - Export tidyselect functions like
`matches()`

or`starts_with()`

(#73). - Add CONTRIBUTING guidelines (#56).
- Add lifecycle badges to functions, soft deprecating
`net_coupler_out()`

,`getExp.coef.permetabolite()`

, and`getExp.coef.out()`

(#59) - Add defensive checks to input arguments with assertive.types (#59).
- Add AppVeyor to repo. Started Travis to run on repo (#61).
- Added function for exposure side estimation:
`nc_exposure_estimates()`

- Major revision of underlying code for generating the outcome-network link estimation (#55), resulting in created and streamlined
`nc_outcome_estimates()`

function. Because of this streamlining, the code is much faster and with the move to use MuMIn we can remove our dependency on rJava via glmulti. - Tidied up
`nc_create_network()`

function so that only the graph skeleton is output (#55). - Started cleaning up, along with leftover files.
- Updated and generated documentation of
`nc_create_network()`

. - Added unit tests for
`nc_create_network()`

and the outcome estimation functions. Travis and code coverage were added as well. - Renamed
`nc_make_network()`

to`nc_create_network()`

and moved into own file. - Modularized
`nc_make_network()`

code and moved into another file.

- Added a
`NEWS.md`

file to track changes to the package. - Added package infrastructure
- Added initial code that other projects use
- Added basic introduction vignette