sbtscs() allows you to create spells ("peace years" in the international conflict context) between observations of some event. This will allow the researcher to better model temporal dependence in binary time-series cross-section ("BTSCS") models.

sbtscs(data, event, tvar, csunit, pad_ts = FALSE)

Arguments

data

the data set with which you are working

event

some event (0, 1) for which you want spells or peace years

tvar

the time variable (e.g. a year)

csunit

the cross-sectional unit (likely a dyad if you're doing boilerplate international conflict stuff)

pad_ts

should time-series be filled when panels are unbalanced/have gaps? Defaults to FALSE.

Value

sbtscs() takes a data frame and returns the data frame with a new variable named spell.

Details

I should confess outright, and it should be obvious to anyone who looks at the code, that I liberally copy from Dave Armstrong's btscs() function in the DAMisc package. I offer two such improvements. One, the btscs() function chokes when a large number of cross-sectional units have no recorded "event." I don't know why this happens but it does. Further, "tidying" up the code by leaning on dplyr substantially speeds up computation. Incidentally, this concerns the same cross-sectional units with no recorded events that can choke the btscs() function in large numbers.

References

Armstrong, Dave. 2016. ``DAMisc: Dave Armstrong's Miscellaneous Functions.'' R package version 1.4-3.

Miller, Steven V. 2017. ``Quickly Create Peace Years for BTSCS Models with sbtscs in stevemisc.'' http://svmiller.com/blog/2017/06/quickly-create-peace-years-for-btscs-models-with-stevemisc/

Author

David A. Armstrong, Steven V. Miller

Examples

if (FALSE) { library(dplyr) library(stevemisc) data(usa_mids) # notice: no quotes sbtscs(usa_mids, midongoing, year, dyad) }