Organizing a quantitative research study
When organizing a quantitative research study, as a quick check, ask the following questions
1. What is your hypothesis (your research question)?
2. What is already known about the problem (literature review)?
3. What sort of design is best suited to studying your hypothesis? (method)
4. What data will you collect to test your hypothesis? (sample)
5. How will you analyse these data? (data analysis)
6. What will you do with the results of the study? (communication)
These questions are broken down in more detail below. (These are mostly taken from Rubin et al. (1990), and have also appeared in Balnaves and Caputi (2001).)
_ What is the goal of the research?
_ What is the problem, issue, or critical focus to be researched?
_ What are the important terms? What do they mean?
_ What is the significance of the problem?
_ Do you want to test a theory?
_ Do you want to extend a theory?
_ Do you want to test competing theories?
_ Do you want to test a method?
_ Do you want to replicate a previous study?
_ Do you want to correct previous research that was conducted in an inadequate manner?
_ Do you want to resolve inconsistent results from earlier studies?
_ Do you want to solve a practical problem?
_ Do you want to add to the body of knowledge in another manner?
Review of literature
_ What does previous research reveal about the problem?
_ What is the theoretical framework for the investigation?
_ Are there complementary or competing theoretical frameworks?
_ What are the hypotheses and research questions that have emerged from the literature review?
_ What methods or techniques will be used to collect the data? (This holds for applied and non-applied research)
_ What procedures will be used to apply the methods or techniques?
_ What are the limitations of these methods?
_ What factors will affect the study’s internal and external validity?
_ Will any ethical principles be jeopardized?
_ Who (what) will provide (constitute) the data for the research?
_ What is the population being studied?
_ Who will be the participants for the research?
_ What sampling technique will be used?
_ What materials and information are necessary to conduct the research?
_ How will they be obtained?
_ What special problems can be anticipated in acquiring needed materials and information?
_ What are the limitations in the availability and reporting of materials and information?
_ How will data be analysed?
_ What statistics will be used?
_ What criteria will be used to determine whether hypotheses are supported?
_ What was discovered (about the goal, data, method, and data analysis) as a result of doing preliminary work (if conducted)?
_ How will the final research report be organised? (Outline)
_ What sources have you examined thus far that pertain to your study? (Reference list)
_ What additional information does the reader need?
_ What time frame (deadlines) have you established for collecting, analysing and presenting data? (Timetable)
Some quantitative research designs
_ Case study: questionnaire, interview, observation. Best for exploratory work and hypothesis generation. Limited quantitative analysis possible.
_ Survey: questionnaire, interview, observation. Best if sample is random.
_ Experiment: questionnaire, interview, observation. Best for demonstrating causality.
Cross-sectional vs longitudinal analysis
All designs can be either cross-sectional or longitudinal.
_ Cross-sectional design involves data collection for one time only.
_ Longitudinal design involves successive data collection over a period of time. Necessary if you want to study changes over time.
Case study designs
_ involves intense involvement with a few cases rather than limited involvement with many cases
_ can’t generalize results easily
_ useful in exploring ideas and generating hypotheses
_ Most popular in business/management research
_ useful when you cannot control the things you want to study
_ difficult to get random and representative samples
_ requires control group to allow for the placebo effect
_ requires the experimenter to control all variables other than the variable of interest
_ requires randomization to groups
_ allows causation to be tested