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)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
.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
adjusted_effect
-> effect_adjusted
)*_with_continuous()
(long form of, the function names, the default unmeasured confounder is Normally distributed)tip_lm()
to tip_coef()
.lm_tip()
to tip_lm()
tip_*
functions into hazard ratio, odds ratio, and relative risktip_coef_with_r2()
, adjust_coef_with_r2()
, and r_value()
lm_tip()
tip()
and tip_with_binary()
. The parameter names are more self-explanatory.broom
package.