`adjust_coef_with_binary()`

now assumes the coefficient is from a linear model rather than loglinear. Use`loglinear = TRUE`

to get the old behavior. (#12, @malcolmbarrett)- Fixed roxygen issue with package documentation
- Update messaging and errors

- Fixed bug, functions based on the
`adjust_coef_with_binary`

function had the old parameter names (`exposed_p`

and`unexposed_p`

). These were changed to match the other new updates from version 1.0.0 to now be`exposed_confounder_prev`

and`unexposed_confounder_prev`

. - Change “relative risk” to “risk ratio” in all documentation.
- Add new JOSS citation

**Breaking changes**. The names of several arguments were changed for increased clarity:

`effect`

->`effect_observed`

`outcome_association`

->`confounder_outcome_effect`

`smd`

->`exposure_confounder_effect`

`exposed_p`

->`exposed_confounder_prev`

`unexposed_p`

->`unexposed_confounder_prev`

`exposure_r2`

->`confounder_exposure_r2`

`outcome_r2`

->`confounder_outcome_r2`

Added two new example datasets:

`exdata_continuous`

and`exdata_rr`

- Make the output tibble names consistent (
`adjusted_effect`

->`effect_adjusted`

)

- Add additional functions that specify
`*_with_continuous()`

(long form of, the function names, the default unmeasured confounder is Normally distributed) - Change
`tip_lm()`

to`tip_coef()`

.

- Changed the name of
`lm_tip()`

to`tip_lm()`

- The API has been fundamentally updated so that the functions now take a numeric value as a first argument rather than a data frame.
- Added adjust_* functions to allow for specification of all unmeasured confounder qualities without tipping
- Split
`tip_*`

functions into hazard ratio, odds ratio, and relative risk - Add R2 parameterization with
`tip_coef_with_r2()`

,`adjust_coef_with_r2()`

, and`r_value()`

- Added ability to perform sensitivity analyses on linear models via
`lm_tip()`

- Updated several function and parameter names. The main functions are now
`tip()`

and`tip_with_binary()`

. The parameter names are more self-explanatory. - The API has been fundamentally updated so that the functions now take a data frame as a first argument.
- There is now explicit (but not required) integration with the
`broom`

package.

- initial CRAN release