RESEARCH METHOD COHEN ok

224 SURVEYS AND DEVELOPMENTAL STUDIES
It is important to consider why respondents may
not reply to requests to participate in surveys.
These might include, for example:
the pressure of competing activities on the time
of the respondent
potential embarrassment at their own ignorance
if respondents feel unable to answer
aquestion
ignorance of the topic/no background in the
topic
dislike of the contents or subject matter of the
interview
fear of possible consequences of the survey to
himself/herself or others
lack of clarity in the instructions
fear or dislike of being interviewed
sensitivity of the topic, or potentially insulting
or threatening topic
betrayal of confidences
losing the return envelope or return address
the wrong person may open the mail, and fail
to pass it on to the most appropriate person.
On the other hand, potential respondents may
be persuaded to participate depending on, for
example:
the status and prestige of the institution or
researcher carrying out the research
the perceived benefit of the research
the perceived importance of the topic
personal interest in the research
interest in being interviewed, i.e. the interview
experience
personal liking for, or empathy with, the
researcher
feelings of duty to the public and sense of civic
responsibility
loneliness or boredom (nothing else to do)
sense of self-importance.
We advise readers to consult Chapter 15 on
questionnaires.
Event history analysis
Recent developments in longitudinal studies include
the use of ‘event history analysis’ (e.g. von
Eye 1990; Rose and Sullivan 1993: 189–90; Plewis
1997; Ruspini 2002). Event history analysis ‘offers
arecordoftheeventsthathavepunctuatedthe
life-course of a group of subjects’ (Ruspini 2002:
5). Such ‘life-courses’ are determined by individual
trajectories and transitions: paths taken and
changes within, and to, paths. An event is a punctuation
or change point. Similarities exist between
event history analysis and longitudinal analysis in
their retrospective nature, taking participants back
through time to identify change moments and
events in their lives. Event history analysis differs
from longitudinal and cross-sectional analysis in
that specific time points for data collection are
not fixed. What drives the analysis is not the time
frame for data collection, but the timing of the
event itself. Whereas longitudinal analysis deals
with discrete and given time periods (e.g. every
six months), event history analysis is timed by
whenever the event occurs. In fixed time frames
it is not always straightforward to ascertain what
happened during atimeperiod.
Event history analysis also uses a set of statistical
techniques whose key concepts include: ariskset
(a set of participants who have yet to experience
aparticulareventorsituation);asurvivor function
or survivor curve (the decline in the size of risk
over time); the hazard or hazard rate (the rate at
which particular events occur, or the risk of a
particular event occurring at a particular time).
The notion of ‘survival’ owes its pedigree to the
origins of event history analysis, in which the
survival time that elapsed was measured between
an animal being giving a drug and the death
of that animal. Further terms include ‘transition
rate’, ‘risk function’, ‘mortality rate’ and ‘transition
intensity’.
Event history analysis suggests that it is
possible to consider the dependent variable in
(e.g. marriage, employment changes, redundancy,
further and higher education, moving house,
death) as predictable within certain time frames
for individuals. The rationale for this derives
from life-table analysis used by demographers to
calculate survival and mortality rates in a given
population over time. For example, if x number
of the population are alive at time t, then it