Estimating support for extremism and its correlates: the case of Pakistan

Publication type

Journal Article


Publication date

June 1, 2014


The extent of support of extremist ideology is a major area of concern for both policy makers
and academic researchers. Identifying the extent and correlates of a difficult to measure
concept such as extremist ideology is often limited by the use of a single imperfect indicator.
This paper outlines one approach, latent class analysis (LCA), to overcome this issue and
uses the example of estimating support for such ideology in Pakistan. Using survey data
from Pakistani men, the level of support is estimated using LCA employing several indicators
related to extremism. The results suggest that although most Pakistanis are not supportive
of extremist ideology, a substantively important portion of men are supportive. LCA also
allows for class assignment, which is useful for understanding covariate relationships
with the latent variable. Based on the results of the LCA, respondents are assigned to
different classifications of extremist support, and a continuation-ratio logistic regression
model is employed allowing for more covariates to be examined. The results suggest that
there are a number of characteristics important in influencing support within this subset of
the population. In particular, younger and less educated men are more likely to support
extremism ideology. The results suggest a potentially useful methodology in understanding
extremism, as well as a greater understanding of the problem of extremist support.

Published in

ASK: Research & Methods

Volume and page numbers

Volume: 23 , p.35 -56






Open Access Journal



Latest findings, new research

Publications search

Search all research by subject and author


Researchers discuss their findings and what they mean for society


Background and context, methods and data, aims and outputs


Conferences, seminars and workshops

Survey methodology

Specialist research, practice and study

Taking the long view

ISER's annual report


Key research themes and areas of interest