Create "peace years" or "spells" by cross-sectional unit, more generally

ps_btscs() 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. It is an improvement on sbtscs() (included in this package) by its ability to more flexibly work with data that have lots of NAs that bracket the observed event data. It is used in the peacesciencer package.

Usage

ps_btscs(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

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

Details

This function is derived from sbtscs(). See documentation there for more information.

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

# \donttest{
library(dplyr)
library(stevemisc)
data(usa_mids)

# notice: no quotes
ps_btscs(usa_mids, midongoing, year, dyad)
#> Joining with `by = join_by(dyad, year)`
#> # A tibble: 14,586 × 7
#>       dyad ccode1 ccode2  year midongoing midonset spell
#>      <dbl>  <dbl>  <dbl> <dbl>      <dbl>    <dbl> <dbl>
#>  1 1002020      2     20  1920          0        0     0
#>  2 1002020      2     20  1921          0        0     1
#>  3 1002020      2     20  1922          0        0     2
#>  4 1002020      2     20  1923          0        0     3
#>  5 1002020      2     20  1924          0        0     4
#>  6 1002020      2     20  1925          0        0     5
#>  7 1002020      2     20  1926          0        0     6
#>  8 1002020      2     20  1927          0        0     7
#>  9 1002020      2     20  1928          0        0     8
#> 10 1002020      2     20  1929          0        0     9
#> # ℹ 14,576 more rows
# }