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A data set on MID onset; illustrates logistic regression

Source: R/ro2001.R
ro2001.Rd

Russett and Oneal (2001) data set used in Rainey (2016) to illustrate compression in logistic regression models. These are the data to reproduce the logistic regression coefficients in Table 2 on p. 11 of the Appendix to Rainey (2016). Note that I've altered the coding of some variables, so the coefficients won't replicate exactly.

Usage

ro2001

Format

A dyad-year data set.

statea

the first state in the dyad

stateb

the second state in the dyad

stateaname

the name of first state in the dyad; created with countrycode

statebname

the second state in the dyad; created with countrycode

year

the year

dispute

a factor variable indicating the onset of conflict, specifically the onset of a militarized interstate dispute

allies

a factor variable indicating whether the members of the dyad are allies or not. Allies are linked by a mutual defense treaty, neutrality pact, or entente.

lcaprat2

the logged ratio of the stronger state's military capability index to that of the weaker member

contiguity

factor variable indicating whether the members of the dyad are contiguous or not

dem.lo

the smaller of the two Polity IV scores in the dyad

logdstab

the logged number of miles between the capitals

power

factor variable indicating whether the dyad is minor powers or at least one member is a great power.

References

Russett, Bruce, and John R. Oneal. 2001. Triangulating Peace: Democracy, Interdependence, and International Organizations. New York: W. W. Norton.

Rainey, Carlisle. 2016. "Compression and Conditional Effects: A Product Term Is Essential When Using Logistic Regression to Test for Interaction." Political Science Research and Methods 4(3): 621–39. doi:0.1017/psrm.2015.59 .

Rainey, Carlisle. 2015. "Replication Data for: Compression and Conditional Effects." doi:10.7910/DVN/ASSC0Y .

Examples


# a simple example

ro <- crdata::ro2001

# glm version of their gee on pp. 314 with no product term
m.noprod <- glm(dispute ~ allies + lcaprat2 + contiguity + dem.lo + logdstab + power,
                family = "binomial", data = ro)

# glm version of their gee on pp. 314 with no product terms
m.prod <- glm(dispute ~ allies + lcaprat2 + contiguity + dem.lo*logdstab + power,
              family = "binomial", data = ro)


# there are no non-contiguous minor powers in this data set
table(ro$contiguity, ro$power)
#>                
#>                 At Least One Great Power Minor Powers
#>   Contiguous                        5348         9423
#>   Noncontiguous                    25225            0