RT Article
T1 Studying Terrorism Empirically: what We Know About What We Don’t Know
JF Journal of contemporary criminal justice
VO 33
IS 3
SP 273
OP 291
A1 Safer-Lichtenstein, Aaron
A2 Loughran, Thomas A.
A2 LaFree, Gary 1951-
LA English
YR 2017
UL https://krimdok.uni-tuebingen.de/Record/1739013565
AB Although the empirical and analytical study of terrorism has grown dramatically in the past decade and a half to incorporate more sophisticated statistical and econometric methods, data validity is still an open, first-order question. Specifically, methods for treating missing data often rely on strong, untestable, and often implicit assumptions about the nature of the missing values. We draw on Manski’s idea of no-assumption bounds to demonstrate the vulnerability of empirical results to different tactics for treating missing cases. Using a recently available open-source database on political extremists who radicalized in the United States, we show how point estimates of basic conditional probabilities can vary dramatically depending on the amount of missing data in certain variables and the methods used to address this issue. We conclude by advocating for researchers to be transparent when building analytical models about the assumptions they are making about the nature of the data and their implications for the analysis and its interpretation.
K1 Point identification
K1 No assumption bounds
K1 Data validity
K1 Missing data
K1 Domestic extremism
K1 Terrorism data
DO 10.1177/1043986217697873