View source: R/whittle_conflicts_jds.R
whittle_conflicts_jds | R Documentation |
whittle_conflicts_jds()
is in a class of
do-it-yourself functions for coercing (i.e. "whittling") conflict-year
data with cross-sectional units to unique conflict-year data by
cross-sectional unit. The inspiration here is clearly the problem
of whittling dyadic dispute-year data into true dyad-year data (like
in the Gibler-Miller-Little conflict data). This particular
function will just drop something, as a kind of nuclear option.
whittle_conflicts_jds(data)
wc_jds(...)
data |
a data frame with a declared conflict attribute type. |
... |
optional, only to make the shortcut work |
Dyads are capable of having multiple disputes in a given year,
which can create a problem for merging into a complete dyad-year
data frame. Consider the case of France and Italy in 1860, which
had three separate dispute onsets that year (MID#0112, MID#0113, MID#0306),
as illustrative of the problem. The default process in peacesciencer
employs several rules to whittle down these duplicate dyad-years for
merging into a dyad-year data frame. These are available in
add_cow_mids()
and add_gml_mids()
.
This really should be the absolute last exclusion rules a researcher uses. It's a "nuclear option", if you will. Assuming you've run other case exclusion rules to isolate onsets and severe disputes, what remains at the end should be duplicates that are functionally equivalent observations. Your data cannot have duplicates, and these remaining observations are basically the same. Therefore, just drop something.
wc_jds()
is a simple, less wordy, shortcut for the same function.
whittle_conflicts_jds()
takes a dyad-year data frame or
leader-dyad-year data frame with a declared conflict attribute type and,
grouping by the dyad and year, returns just those observations that
have the lowest start month.
Steven V. Miller
Miller, Steven V. 2021. "How peacesciencer Coerces Dispute-Year Data into Dyad-Year Data". URL: http://svmiller.com/peacesciencer/articles/coerce-dispute-year-dyad-year.html
# just call `library(tidyverse)` at the top of the your script
library(magrittr)
gml_dirdisp %>% whittle_conflicts_onsets() %>% whittle_conflicts_jds()
cow_mid_dirdisps %>% whittle_conflicts_onsets() %>% whittle_conflicts_jds()
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