Changes include:
{stevemisc}.
This comes as later versions of R balk at the use of
order() on data frames.download_extdata() will download some augmented dyadic
minimum distance data for CoW and G-W states from 1886 to 2019.tss_rivalries as updated rivalry data from 1494 to
2020.atop_alliance and
cow_alliance. It’s less of a {peacesciencer}
bug, per se, but the raw data that were presented as directed were
actually not directed at all. They are now.add_cow_alliance() that did not honor
the temporal bound of the alliance data (i.e. 1816-2012). My b.This version has a few odds and ends and a version accelerated to 1.0.0 to coincide with the acceptance of a manuscript describing this package in Conflict Management and Peace Science.
add_cow_mids() and add_gml_mids()
about the default case-exclusion rules for dyadic analyses.add_fpsim() and
download_extdata() for more.cow_nmc) to
version 6.0.cow_ddy and gw_ddy, since it’s 2022
now.grh_arms_races for arms race data.ps_bib.ps_cite() to no longer depend on
{bib2df}. With it, remove {bib2df} as a
package dependency.This is a leader-intensive update. Additions/new features include:
LEAD: a data set on select leader experience and
attribute descriptions (LEAD).lwuf: a data set from Carter and Smith
(2020) measuring leader willingness to use force.download_extdata() now also downloads directed leader
dyad-year data for all directed leader dyad-years from 1870 to 2015. The
data come in two forms. One is all possible (inter-state,
leader-overlap) dyadic leader pairings from 1870 to 2015, as presented
in the Archigos data. The second standardizes these data to the CoW
state system data. It also downloads directed dyad-yer data of
chance-corrected measures of dyadic foreign policy similarity. Type
?download_extdata() in the R session after updating for
more information.create_leaderdyadyears(): create leader dyad-year data
(via archigos) for all leader dyad-year combinations from
1870 to 2015. This function leans on remote data available for download
in download_extdata(). The function returns either all
possible Gleditsch-Ward dyadic leader pairings (standardized to
Gleditsch-Ward state system dates) or standardizes the Archigos data to
Correlates of War state system member data.gml_part: a data set on participant summary information
from the GML MID data.add_fpsim() adds estimates of dyadic foreign policy
similarity to your dyad-year and leader-dyad-year data.add_gml_mids() now works with leader-year data. See
documentation for more.add_spells() will do more general peace spell
calculations, though this package will now depend on v. 1.3.0 of
{stevemisc}.add_lwuf() adds estimates of leader willingness to use
force to leader-year and leader-dyad-year analyses.add_lead() adds some leader attributes to leader-year
or leader-dyad-year analyses.gml_mid_dirleaderdisps and
gml_mid_ddlydisps include data on leader dyads in
conflict.declare_attributes() allows users to declare
package-specific attributes to outside data they bring to the R session.
This allows the user to use many of the shortcuts in this package to
their data.ps_version() will display version information about the
data included in this package.false_cow_dyads and false_gw_dyads list a
handful of dyads that appear in the same year, but never on the same day
in the year. They’re used for anti-joining in
create_dyadyears().leader_codes matches, as well as one can,
leader/observation codes in Archigos 4.1, Archigos 2.9, and the LEAD
data.Other changes include:
add_creg_fractionalization(),
add_rugged_terrain(), add_democracy(), and
more. Some functions, like add_gml_mids(), can be anchored
explicitly to leader-level units of analyses. Several other functions
(e.g. add_sdp_gdp() and others like it) are fundamentally
still state-year or dyad-year functions the extent to which leaders are
still nested in states and leader-dyads are just a derivation of
inter-state dyads (i.e. leaders are nested in states). Use with some
caution with that in mind, though these functions are still useful for
leader-level analyses that are interested in some of these covariates
for making state-to-state comparisons on top of leader-level
analyses.cow_sdp_gdp and gw_sdp_gdp are
now rounded to three decimal points. These “economic” data are routinely
the biggest in the package, and it’s because of the decimal points. The
justification for this is these data are estimated/simulated anyways and
the information loss is at the 1/1000th decimal point. This procedure
basically cuts the size of the data to be less than 25% of its original
size. This is a huge reduction in disk space.leader_year) is now an attribute. Where
appropriate, leader-year and state-year functions are treated the same.
For example, the GDP data contained in add_sdp_gdp() are
fundamentally state-year, but perhaps a leader-year control of interest
even as leaders are nested in states.leader_dyad_year) is now an
attribute. Where appropriate, leader-year and leader-dyad-year functions
are treated the same. Where possible/tractable, leader-dyad-year data
are explicitly anchored to leader-level units of analysis
(e.g. add_gml_mids(), prominently).create_leaderyears() works on the observation ID and
not the leader ID. Observation IDs are unique to each leader-period, but
leader IDs are not.add_peace_years() has been superseded by
add_spells(). The “superseded” language communicates the
function will still work as it has for previous releases, for data types
supported by the function, though its development will stop.
add_spells() promises to have greater functionality.
Communicating these changes via badges brings in
{lifecycle} as an imported package.archigos data’s ccode has been renamed to
gwcode to reflect these are actually Gleditsch-Ward state
codes.create_leaderyears(), create_dyadyears(),
and create_stateyears() have a built-in argument for
subsetting the years returned by the function
(subset_years). Use to your discretion.cow_mindist and gw_mindist data,
given new {cshapes} updates. Data now run from 1886 to
2019.cow_capitals and gw_capitals data.
Remove capitals data for redundancy. Both capital data sets
extended to 2020.add_capital_distance() now works with Correlates of War
and Gleditsch-Ward data, both dyad-year and state-year.add_atop_alliance() that added 0s to years
after the ATOP domain. Thanks to @joshuaalley for pointing this out.{lubridate}. Earlier versions of this package uncritically
leaned on {lubridate} for functions I could either write
myself (i.e. year(), which is now
.pshf_year()) or were already duplicated in base functions
in R (i.e. ymd(), a wrapper for as.Date() as I
use it). With it, {lubridate} is no longer a requirement
for this package.gml_mid_disps.ps_conflict_type attributes for some conflict data
(e.g. CoW-MID, GML).add_cow_mids() and add_gml_mids().whittle_conflicts_onsets(),
whittle_conflicts_fatality(),
whittle_conflicts_hostility(),
whittle_conflicts_duration(),
whittle_conflicts_reciprocation(),
whittle_conflicts_startmonth(), and
whittle_conflicts_jds(). These are admittedly gnarly
function names to type out if you don’t have an IDE like RStudio to
assist you. Thus, these respective functions come with shortcuts of
wc_ (e.g. wc_onsets()). Check the package
documentation to see what these are.show_duplicates() as a diagnostic tool. This
function is useful for users who want to do some advanced stuff with
data created in {peacesciencer} (e.g. merging in custom
data) and want to see if they botched a merge by creating duplicate
observations.archigos data
frame now includes some more information about leaders (e.g. name,
gender, and year of birth). create_leaderyears() will
create leader-year data as well. The next update will expand more on
leader functions. For now, the ensuing output from this function is
treated as synonymous to state-year data.download_extdata() as a way of side-stepping
package space limitations. Some files will have to be stored remotely
and then loaded at the user’s discretion, which is what this function
will do. This was largely brought on by the CoW trade data
(cow_trade_ndy), which is also removed in this update. More
data may have to be moved remotely in the future, though this package
will endeavor to keep this to a bare minimum. Importantly,
download_extdata() keeps inventory of what it is
downloading. Data information is included therein. This develop does
implicitly assume that the directory in which this package is installed
is writable by the user. For like 99% of users, this shouldn’t be a
problem (and executing .libPaths() should confirm that). Do
reach out if it is.creg data frame.{bib2df} as package dependency. Force upgraded
version of {stevemisc} as package dependency.LazyDataCompression: xz to DESCRIPTIONcreate_dyadyears(),
create_statedays(), and
create_stateyears().add_cow_wars() function.add_ccode_to_gw(). Fix underlying data for
cow_gw_years. Add gw_cow_years.add_strategic_rivalries().add_ucdp_acd(). With it, update
ucdp_acd data for functionality.add_rugged_terrain().cow_trade_ndy data. With it, update
add_cow_trade() function for speed upgrades.cow_war_inter, cow_war_intra
data.creg data.gwcode_democracy data. add_democracy()
now takes CoW or G-W data.hief data.rugged data.td_rivalries data.ps_cite() and ps_bib. Remove
citations.cow_sdp_gdp and gw_sdp_gdp. Update
add_sdp_gdp() to reflect this change.add_contiguity() for why
non-contiguous dyads are 0s and not 6s. Briefly: I don’t think of these
data as ordinal and I don’t encourage the researcher to think of them as
ordinal either.add_peace_years(), which now works with UCDP
conflict data.filter_prd() is now a shortcut for
add_contiguity() and/or add_cow_majors() if it
is called near the top of the pipe (i.e. before the user executed the
commands required to calculate politically relevant dyad status).add_nmc() (and cow_nmc). -9 is
now explicitly NA, as it should have been.add_peace_years(), which can now be used anywhere
in the chain of commands (instead of just last).
add_peace_years() is also a bit more “general” and includes
a derivation of the sbtscs() function from the
{stevemisc} package.add_minimum_distance() and add_sdp_gdp().
These merges now lean on system attributes declared in
create_dyadyears() and
create_stateyears().add_mids(). Use add_gml_mids()
instead.cow_ddy and its documentation.cow_mid_ddydisps, cow_mid_dirdisps,
and cow_mid_disps data.gml_mid_ddydisps data.add_cow_mids() function.add_gml_mids() function.add_peace_years() function.add_mids(). Use add_gml_mids()
instead.ps_data_type == "dyad_year" as attribute to
cow_mid_dirdisps and gml_dirdisp. This allows
{peacesciencer} functions for these data sets.atop_alliance (directed dyad-year) dataarchigos datacow_sdp_gdp and gw_sdp_gdp dataucdp_acd dataucdp_onsets dataadd_archigos() functionadd_atop_alliance() functionadd_minimum_distance() function. For now, this has
no default. You must specify “gw” or “cow”.add_sdp_gdp() function. For now, this has no
default. You must specify “gw” or “cow”.add_ucdp_onset() function.filter_prd(). Past versions of my code had
treated non-contiguous dyads as 6s. Here, they’re 0s. That created
situations where I wasn’t filtering anything at all with this
function.cow_alliance to distinguish from
ATOP equivalents.create_statedays() function.