- #102 add import tags for `log_transform()` and link to equivalent functions, apply default argument values / checks
- #97 rename out argument

- equivalent to `pred_to_z()`
- #102 write documentation

- #118 adapt response variable preparation to accept additional argument `dataset_log_transform` apply argument checks #116, add roxygen param #102
- #118 adapt response variable processing to accept either/or/none for dataset standardisation/log-transformation.

- #102 add import, return, and see also roxygen doc tags, replace note with details tag, rename fn doc title
- #116 update argument checks conditional expression
- #118 match output to `log_transform_yi()` (now returns additional cols `lower` and `upper`, not only `c("Z","VZ")`)
- #118 match process to `log_transform_yi()` and #97 generalise processing to both euc/bt datasets without hard-coding dataset names in fns, and remove associated dataset-specific argument checking #116

- #116 check appropriate required variable (i.e. function needs `back_transformed_data`, but checked for `augmented_data` in `dat` arg, wouldn't throw required error because `augmented_data` was present in `dat`

…dardisation updates

- #118 extract `lower` and `upper` transformed vals in line with addition of `log_transform_response()` / changes to `standardise_response()`

- #118 add log-transformation equivalent to `standardise_response()` and `process_resonse()`
- #102 add function documentation, including examples

…pipeline

- #118 call new arg `dataset_log_transform` in fn to log-transform outcomes for euc yi analysis

…ddition

- #118 ensure application of Z_VZ_preds takes the generalised colnames yi, yi_se instead of using hard-coded dataset application #97

…lied for standardising / transformation

- accidentally deleted when upgrading for #118, have added creation of transform_datasets tibbles for all cases now, and then these will apply the appropriate functions in final code chunk at end

- `dat` to `data` to help with auto-matching in pmap within prepare_response_variables() wrapper #118
- ensure all family fns have ... arg for pmap application in prepare_response_variables() since all fns have different argument lengths and names

…ample code for `log_transform_response()`

… of transformation / standardisation in `standardise_response()`

- #118 delete old pmap helper function

…fter #118 updates

---

For `ManyEcoEvo_yi` currently which does not have an `estimate_type` col

…ype` is missing in `ManyEcoEvo` dataframe

- #118 build: devtools::document()

…ew name

----

Was returning only the first column as a vector rather than entire output of log_transform_yi() because `ifelse()` returns vectors dummy!

…ponse_variables() that now create estiamte_type col

---

unnest() was throwing an error after splitting based on scenario numbers because colum estimate_type was duplicated

…erenc `VZ` colnames (i.e. from `log_transform_response()`) #118

- refactor!: `apply_VZ_exclusions()` to handle different out-of-sample colnames for each dataset #118

Switch to `@importFrom` tags from `@import`

Add `@seealso`, `@details` and some `@examples`

Reorganise index manual grouping structure with `@family` and `@describeIn` tags

`devtools::document()`

Refs: #97 #102

…s::document()`

- Add `@import` and `@importFrom` tags
- Update `@details` with behaviour explanations after removing comments
- Add `@family` tag for utility functions
- Add `@seealso` tags

style!:

- line-spacing / tabs
- explicitly call `by =` arg for joins

style: remove todo comments #97, shutup noisy joins by supplying `by` arg in join call.

…rceded and add arg checking #116

style: linespacing / and indentation #97

- switch arg to `data` from `ManyEcoEvo`
- expose argument to user `n_min` and `n_max`
- explicit join by argument in join
- ensure filter diversity_indices for each reduced subset
- ensure filter diversity_data on effects_analysis and NOT data

---

This step filters datasets into a `'effects_analysis'` column, and therefore any filtering of the `diversity_*` data must be based on `effects_analysis`

refs: #102 #97

- expose filtering of subsets to user argument: ignore outlier generation for some subsets
- Expose `n_min` and `n_max` args to user
- Add argument checks #116, inc. checking filter expressions for existance of col names in `data`
- Conditionally slice depending on whether `n_*` args supplied in call
- Define internal helper fns to reduce duplicate code
- Permit multiple logical expressions in argument ignore_subsets
- Allow different values of `n_min` and `n_max` for different `dataset`s

bug!: properly evaluate whether arg `ignore_subsets` is null and parse to `filter_vars`, see `dplyr::dplyr_data_masking`

docs!: Update docs #118

- include functional updates in roxygen docs #102
- rm targets pipeline family tag

style: tidy lint #97

- linespacing / whitespace
- rm TODO comments
- Add section header comments

bug: comment typo

…itch to `c()`

… for `Zr` case (i.e. when `estimate_type` is supplied).

---

Adding in ungrouping caused transmute to ditch id / subset grouping vars

docs: Add `@details` and @import*` tags

refs: #97

bug!: #118 ensure `estimate_type` column is added back in using argument value if existing col is replaced and stop grouping on returned data frame

- rm commented out `poss_fit_*()` (now exported internally in 7dabe6d) #97
- replace name of data arg to `data` #97
- switch to rlang::is_null for arg checking #116 / conditional behaviour
- Add arg checking for `filter_vars`, `data`, and checking wither required columns, incl. those in `filter_vars` exist in `data` #116
- expose user-supplied arguments `outcom_variable` / `outcome_SE` and match values to arg conditions in new columns
- update supply of colnames arg to meta-analysis functions

docs!: update corresponding docs #102

- switch to `@importFrom` for `cli::`, add missing `@importFrom` calls
- Add `@details` on user-specified exclusion of outcome variable / outcome variable SE

style: spacing indentation, rm inline TODO comments #97

…118

- `fit_MA_mv()` switch from `Z_colname` to `outcome_colname` and `VZ_colname` to `outcome_SE_colname` #118
- `calculate_deviation_score()` #118:  expose colname selection column to user , return meta-analytic mean in column, add `outcome_colname` to specify relevant outcome column name, add argument checking #116
- `apply_slice_conditionally()` create column `exclusion_set` if does not exist and switch to `se_log` as `VZ_colname` in example for eucalyptus` #188
- `box_cox_transform()` expose `outcome_SE_colname` arg, add relevant arg checks, update cli output, parse outcome_SE_columns` to `folded_params()` function call #188
- replace `std.error_log` arg with `se_log` for any logged `yi` data #188
- and update wrapper function calls in `meta_analyse_datasets()`, provide NULL default for new arg `outcome_SE` #188
- `fit_box_cox_ratings_cat()`: add arg checks #116, replace arg name `.data` with `data`, switch to `inject` approach as per `fit_box_cox_ratings_cont()` #97
- fit_box_cox_ratings_cont()` switch to `data` arg from `.data`, add arg checks #116
- add arg checks to `standardise_response()`, `fit_sorensen_glm()`, `fit_multivar_MA()` , `fit_uni_mixed_effects()` #116

docs!: update corresponding docs

- delete obsolete `@examples` code #102
- add #TODO comments #97
- add missing `@import` calls
- switch to `@importFrom` from `@import` for `purrr::` `rlang::` and `tidyr::` et al
- don't import `rlang::` in package.R

bug!: minor bug fixes

- unquote bare colname in pointblank check for `exclude_extreme_VZ()`
- `fit_metafor_mv_reduced()` replace obs_id with study_id as random effect

- add import tag for `purrr::transpose()` in `fit_multivar_MA()` #102
- defuse argument `outcome` in `cli()` call in `fit_boxcox_ratings_cont()`

- `meta_analyse_datasets()`:
  - use correct argument in calls to `fit_boxcox_ratings_*()` (`data` from `.data`)
  - apply coalesce on list-cols only and `@import` `tidyselect::where()` (previously non-list-cols were ignored because character columns were explicitly grouped, however current approach in pipeline is ungrouped in order to allow for generalisability / scalability #87. Can't caoalesce a character vector and list, must be of same type).

build!: update calls in targets `yi` pipeline

style: fix indenation

- style: use comments to structure function. rearrange condition checks, and helper functions. update indentation. #97

style: fix indentation and spacing #97

style: fix indentation, spacing, reorganise subsections

---

See <https://books.ropensci.org/targets/random.html>

refs: #97