RESEARCH METHOD COHEN ok

6
Validity and reliability
There are many different types of validity and reliability.
Threats to validity and reliability can never
be erased completely; rather the effects of these
threats can be attenuated by attention to validity
and reliability throughout a piece of research.
This chapter discusses validity and reliability in
quantitative and qualitative, naturalistic research.
It suggests that both of these terms can be
applied to these two types of research, though how
validity and reliability are addressed in these two
approaches varies. Finally validity and reliability
are addressed, using different instruments for data
collection. It is suggested that reliability is a
necessary but insufficient condition for validity
in research; reliability is a necessary precondition
of validity, and validity may be a sufficient but
not necessary condition for reliability. Brock-
Utne (1996: 612) contends that the widely
held view that reliability is the sole preserve
of quantitative research has to be exploded,
and this chapter demonstrates the significance
of her view.
Defining validity
Validity is an important key to effective research.
If a piece of research is invalid then it
is worthless. Validity is thus a requirement for
both quantitative and qualitative/naturalistic research
(see http://www.routledge.com/textbooks/
9780415368780 – Chapter 6, file 6.1. ppt).
While earlier versions of validity were based on
the view that it was essentially a demonstration
that a particular instrument in fact measures what
it purports to measure, more recently validity has
taken many forms. For example, in qualitative data
validity might be addressed through the honesty,
depth, richness and scope of the data achieved, the
participants approached, the extent of triangulation
and the disinterestedness or objectivity of the
researcher (Winter 2000). In quantitative data validity
might be improved through careful sampling,
appropriate instrumentation and appropriate statistical
treatments of the data. It is impossible
for research to be 100 per cent valid; that is the
optimism of perfection. Quantitative research possesses
a measure of standard error which is inbuilt
and which has to be acknowledged. In qualitative
data the subjectivity of respondents, their
opinions, attitudes and perspectives together contribute
to a degree of bias. Validity, then, should be
seen as a matter of degree rather than as an absolute
state (Gronlund 1981). Hence at best we strive to
minimize invalidity and maximize validity.
There are several different kinds of validity
(see http://www.routledge.com/textbooks/
9780415368780 – Chapter 6, file 6.2. ppt):
content validity
criterion-related validity
construct validity
internal validity
external validity
concurrent validity
face validity
jury validity
predictive validity
consequential validity
systemic validity
catalytic validity
ecological validity
cultural validity
descriptive validity
interpretive validity
theoretical validity
evaluative validity.