[x] TMLE calculates all implemented measures (RD, RR, OR) at once. Saves computation time if the user wants multiple measures and is fitting a time-intensive ML algorithm #39
[x] Fixing standard_mean_difference for categorical variables. Will need to use patsy to parse out categorical variables via C(...), otherwise "I" cannot know which variables are categorical #59
[x] Adding stochastic treatments for binary exposures for TimeFixedGFormula via fit_stochastic() Allows for both unconditional and conditional probablities #58
[x] Add continuous outcomes to TimeFixedGFormula but this time actually get it to work as intended. Need to think through the set up for the two potential interventions (threshold vs. shift) delaying this again... #49
[ ] Also learn ReadTheDocs for the Reference papge (still not doing what I hoped it would)
Updating to version 0.4.2
[x]
TMLE
calculates all implemented measures (RD, RR, OR) at once. Saves computation time if the user wants multiple measures and is fitting a time-intensive ML algorithm #39[x] Fixing
standard_mean_difference
for categorical variables. Will need to use patsy to parse out categorical variables viaC(...)
, otherwise "I" cannot know which variables are categorical #59[x] Adding stochastic treatments for binary exposures for
TimeFixedGFormula
viafit_stochastic()
Allows for both unconditional and conditional probablities #58[x]
Add continuous outcomes todelaying this again... #49TimeFixedGFormula
but this time actually get it to work as intended. Need to think through the set up for the two potential interventions (threshold vs. shift)[ ] Also learn ReadTheDocs for the Reference papge (still not doing what I hoped it would)