campaign_long: Long-format Data on Negative Campaign Advertising in US...

In rbw: Residual Balancing Weights for Marginal Structural Models

Long-format Data on Negative Campaign Advertising in US Senate and Gubernatorial Elections

Description

A dataset containing 19 variables and 565 unit-week records on the campaign of 113 Democratic candidates in US Senate and Gubernatorial Elections from 2000 to 2006 (Blackwell 2013).

Usage

campaign_long

Format

A data frame with 565 rows and 19 columns:

demName

name of the Democratic candidate

d.gone.neg

whether the candidate went negative in a campaign-week, defined as whether more than 10% of the candidate's political advertising was negative

d.gone.neg.l1

whether the candidate went negative in the previous campaign-week

camp.length

length of the candidate's campaign (in weeks)

deminc

whether the candidate was an incumbent

base.poll

Democratic share in the baseline polls

base.und

share of undecided voters in the baseline polls

office

type of office in contest. 0: governor; 1: senator

demprcnt

Democratic share of the two-party vote in the election

week

week in the campaign (in the final five weeks preceding the election)

year

year of the election

state

state of the election

dem.polls

Democratic share in the polls

dem.polls.l1

Democratic share in the polls in the previous campaign-week

undother

share of undecided voters in the polls

undother.l1

share of undecided voters in the polls in the previous campaign-week

neg.dem

the proportion of advertisements that were negative in a campaign-week

neg.dem.l1

the proportion of advertisements that were negative in the previous campaign-week

id

candidate id

References

Blackwell, Matthew. 2013. A Framework for Dynamic Causal Inference in Political Science. American Journal of Political Science 57(2): 504-619.

rbw documentation built on March 18, 2022, 5:35 p.m.