Currently, clear_lastminute_nas will remove any row which has any NA's in it whatsoever. With multiple signals, this can mean removing rows with real data (as an example, see 11-29-24, for which 10-02-24 is the last day with data). Before using chng, we will need another scheme to handle differently missing data. Ideas:
locf NA's in non-outcome signals. This is not a great idea, as lags likely become meaningless.
do the equivalent of extend_ahead but for lags (e.g. if the last observation for chng is 30 days behind, adjust the lags of c(0,7,14) to c(30,37,44).
?
@brookslogan may have other thoughts I forgot about.
Currently,
clear_lastminute_naswill remove any row which has anyNA's in it whatsoever. With multiple signals, this can mean removing rows with real data (as an example, see11-29-24, for which10-02-24is the last day with data). Before usingchng, we will need another scheme to handle differently missing data. Ideas:NA's in non-outcome signals. This is not a great idea, as lags likely become meaningless.extend_aheadbut for lags (e.g. if the last observation for chng is 30 days behind, adjust the lags ofc(0,7,14)toc(30,37,44).@brookslogan may have other thoughts I forgot about.