Research Design
Edouard Manet: The Bar at the Folies Bergere, 1882
Three Purposes of Research
1. Description
• Basic facts about an area of interest.
• Learn the range of behavior.
• Learn need for possible applied programs.
2. Exploration
•
•
•
•
•
Examination of a new interest area.
Need for a better understanding of an area.
Test the feasibility for further research.
Develop measures and methods.
NOT an excuse for sloppy research.
Three Purposes of Research
3. Explanation
• Explain why events occur.
• Predict future events.
• The ability to explain and predict lends
credibility to the development of programs
designed for social change.
• Given that science is distinctive from other
ways of knowing because of its reliance upon
theory, explanation can be considered the goal
of science.
The Logic of Nomothetic Explanation
1. Nomothetic Explanation
• Explanation of cause and effect.
• Focus on key determinants of an event.
2. Criteria for Nomothetic Causality
• Correlation: Empirical correspondence
between two variables (e.g., as one variable
increases, another variable increases).
• Time Order: The independent variable
precedes the dependent variable in time.
• Nonspurious: The relationship between two
variables is not caused by a third variable.
The Logic of Nomothetic Explanation
3. False Criteria for Nomothetic Explanation
• Nomothetic explanation is probabilistic, not
complete (without exceptions).
• Exceptional cases do not refute nomothetic
explanation.
4. Necessary and Sufficient Causes
• Necessary: Condition that must be present for
the event to occur.
• Sufficient: Condition that guarantees an event
will occur.
The Logic of Nomothetic Explanation
5. Unit of Analysis
• Whom or what is being studied.
• Not necessarily the unit from which data is
collected because one might want to aggregate
individual data.
• Example: One might examine community
social cohesion across 100 communities by
asking 150 persons in each community about
their sense of belonging to their neighbors and
the community. In this case, the unit of
analysis is the community (n = 100).
Research Design
1. Cross-Sectional Studies
• Observations taken at one point in time.
• Explanation occurs by examining differences
across the units of analysis.
• Example: Self-esteem and marital satisfaction
are measured for 100 individuals at one point
in time. The hypothesis: The greater the selfesteem, the greater the marital satisfaction is
tested by the correlation between self-esteem
and marital satisfaction for the 100 individuals.
Research Design
2. Longitudinal Studies
• Observations are taken more than once.
• Explanation occurs by examining differences
across time.
• Example: Self-esteem and marital satisfaction
are measured for 100 individuals at two points
in time. The hypothesis: The greater the selfesteem, the greater the marital satisfaction is
tested by examining changes in self-esteem
and changes in marital satisfaction across time
for the 100 individuals.
Research Design
3. Trend Studies
• A longitudinal study that examines changes in
a population across time.
• Each study collects data from different
individuals.
• Example: In 2003, 1,000 people are asked for
their support of same-sex marriage. In 2013, a
different set of 1,000 people are asked for their
support of same-sex marriage. The difference
in opinions is the trend in support for same-sex
marriage.
Research Design
4. Cohort Studies
• A longitudinal study that examines changes in
a cohort across time.
• Each study collects data from different
individuals within the same cohort.
• Example: In 2003, 1,000 people, ages 18-37,
are asked for their support of same-sex
marriage. In 2013, a different set of 1,000
people, ages 28-47, are asked for their support
of same-sex marriage. The difference in
opinions is the cohort support for same-sex
marriage within this cohort of individuals.
Research Design
5. Panel Studies
• A longitudinal study that examines changes in
individuals across time.
• Each study collects data from the same
individuals.
• Example: In 2003, 1,000 people are asked for
their support of same-sex marriage. In 2013,
the same 1,000 people are asked for their
support of same-sex marriage. The difference
in opinions is the change in support for samesex marriage.
Research Design
5. Panel Studies (Continued)
• Panel studies provide the opportunity for more
in-depth analysis.
• For example, one can examine the key
determinants of changes in opinions because
one is collecting data from the same
individuals.
• Longitudinal panel studies are very expensive,
but very informative forms of research.
• One must account for attrition as each “wave”
of data is collected from the panel of subjects.
Research Design
6. Approximating Longitudinal Studies
• Sometimes, longitudinal explanation can be
inferred from a cross-sectional study.
• For example, questions might be asked
regarding history of alcohol and drug use. One
might find, for example, that all persons who
use cocaine also smoke marijuana and drink
alcohol. And, some persons might smoke
marijuana and not use cocaine, but all of these
persons drink alcohol. One might infer a
progression in behavior from drinking alcohol to
smoking marijuana to using cocaine.
Research Design
Summary
• Each research design has its advantages and
disadvantages.
• A cross-sectional study is the least expensive
to implement, but presents the most difficulty in
determining cause and effect.
• Longitudinal studies are more expensive to
implement, but provide a better sense of cause
and effect.
Research Design
Summary
• A trend study, such as analysis of decennial
census data, provides information on changes
in a population over time. It can be difficult to
understand why change occurred, however,
because one is not collecting information from
the same individuals over time.
• A cohort study provides more detail than does
a trend study, but still presents problems for
determining cause and effect because the
same persons are not studied over time.
Research Design
Summary
• A panel study collects information from the
same persons over time, thereby providing the
best form of research design for determining
cause and effect.
• A panel study, however, is difficult and
expensive to implement.
How To Design a Research Project
1. Getting Started
• Literature review
• Learn the key issues and main theoretical
perspectives used to examine these issues.
• Learn which types of research have been
the most productive.
• Learn what kinds of research are needed.
• Learn the key methods used in this area.
• Data availability
• Learn what data are available for analysis.
• Learn the limitations of collecting data.
How To Design a Research Project
2. Conceptualization
• Decide which key concepts need to be
measured.
• This decision rests mainly with deciding which
extant theories to use or how one wishes to
develop new theories.
• Evaluate the levels of validity and reliability
found in previous studies for your concepts of
interest.
How To Design a Research Project
3. Choice of Research Method
• Decide whether the study will be quantitative,
qualitative, or some combination of these. This
decision rests with what you want to learn from
the research, not upon your opinion of what
type of research is “better overall.” What is
“better overall” is to select the appropriate
method for the task at hand.
• It can be very difficult to conduct survey
research if one does not have a good sense of
the content validity of one’s concepts.
How To Design a Research Project
4. Operationalization
• Decide how to measure your concepts.
• This task is not always so straightforward as it
might seem.
• It can be very difficult to design a valid and
reliable measure of even simple concepts.
• Sometimes, it is necessary to ask indirect
questions to avoid a normative response.
• “When do you give coca to animals?”
• “Do you want your children to have the
same job that you have? same job as you?”
How To Design a Research Project
5. Population and Sampling
• The population is the group about whom we
want to draw conclusions.
• Sampling of this population can involve several
steps, with decisions to be made for each step.
6. Observations
• Collecting data involves many steps and many
decisions.
• Data collection might be done overnight, or
might take years to accomplish.
How To Design a Research Project
7. Data Processing
• Quantitative data analysis might entail just the
calculation of descriptive statistics or it might
entail using highly sophisticated procedures.
• Qualitative data analysis might rely simply
upon field notes, or it might use sophisticated
software designed for such analysis.
8. Application
• Reporting results to the community of scholars.
• Designing programs for social change.
The Research Proposal
1. Problem or Objective
• What is to be accomplished?
2. Literature Review
• What has been done so far?
• Work on the “missing brick.”
3. Subjects for Study
• Who will be studied?
4. Measurement
• What are the key variables?
• How will they be measured?
• How do your measurements compare with
ones in previous literature?
The Research Proposal
5. Data Collection Methods
• How will the data be collected?
• Why was this method chosen?
6. Analysis
• How will the data be analyzed?
• Will you focus on description or explanation?
7. Schedule
• When will the data be collected?
• What is the timeline for the study?
8. Budget
• How much money is needed?
• How will it be spent?