1. Important Sections of the Methodology Chapter in the Dissertation
Method Kazaura, PhD

4. Methodology

5. A methodology Explaining how you carried out your research
Where your data come from
Type of data gathering techniques used, etc
It is an instruction manual of your plasma TV

6. A methodology Third party gets enough information to replicate a study
Do not have to include tools
Shows why you chose to use those particular techniques
What new information to collect

7. Methodology (points):
Introduction
Study design
Study area
Target population
Study population
Sample size
Sampling procedure
Study instruments

8. Methodology (points): Ctn
Data collection procedure
Pre-testing of tools
Recruitment of Ras
Management of tool in the field
Data sorting and editing
Data entry
Data processing and analysis

9. Methodology (points): Ctn
Variables (Dependent and Independent)
Ethical issues

10. Introduction Summary of the research questions
Brief aims and objectives of your study in relation to the methodology

11. Study types Quantitative or qualitative or both approaches
Exploratory or
Descriptive study
Knowing that a problem exist but know little about its characteristics or possible causes
Cross-sectional comparative
Case-control
Cohort
Suspect that certain factors contribute to the problem
Analytical studies
Know factors, you want to the extent to which a particular factor causes/ contributes to the problem
Cohort study
Experimental or
Quasi experimental study
Knowing the cause, develop or assess an intervention to prevent or solve the problem
Quantitative or qualitative or both approaches

12. Study area Bring the reader to understand your study area
Relevant information only

13. Target population
The population into which inference would be made

14. Study population
The actual sample you will collect data

15. Sample size estimation
Probabilistic or non-probabilistic
“Convenient”?
Right formula (necessary to show a formula?)

16. Sampling procedure Clear, step-by-step
If more than one population, have separate sub-section

17. Stratified VS Cluster sampling4
STS: Take a sample in each stratum
CLS: Fully study all units in a selected cluster

18. Study instruments

19. Data collection tools Using secondary data? Observational?
Primary data (Interviewing)?
Self-admin or face-to-face?
Focus group discussions or IDI?

20. Data collection tools Can use a combination of these
Each has advantages and disadvantages
Try to minimize BIAS (distortion of the collected data – away from reality)
Observer bias, defective instrument, information bias, etc
Language and procedure to get a final version

21. Questionnaires Take objective and variables as a starting point
Formulate a question that captures both
A question should measure one thing at a time
No leading questions
Avoid vague terms (“unhealthy food”)
Get the proper sequencing (flow) of questions
Ask sensitive questions in a socially acceptable way
(“If your friend was considering abortion, what would you advise her”)

22. Questionnaires Open-ended questions Semi structured questions
What do you think are the reasons for not breast-feeding?
Semi structured questions
Example….
Closed questions
Example

23. Variables What new information are we going to collect?
Background variables (maybe independent variables)
Dependent variables
Confounding variables
Remember, types of variables will dictate the type of analysis (handling of variables)

24. Variables How are you going to measure them?
Operational definition of variables

25. Data collection procedure
So as to help improve the usefulness, timeliness, and accuracy of data
These procedures describe processes that will result in high quality data
Who to do what
How
Imagine you are planning to conduct ‘exit interviews’

26. Recruitment of RAs and Pre-testing
RA: who are they and why?
Pilot and pre-testing of instruments

27. Management of data in the field
What to do after a completed questionnaire?
Safe custody
Data sorting and editing
Data entry

28. Processing and analysis
Sort data
Perform quality checks
Data processing (master sheets or Epi Info)
Categorizing
Coding (new variables or for open ended questions)
Summarizing data into master sheets or data entry

29. Data analysis Describe variables (frequency tables)
Based on objectives, cross-tables?
Select (decide) appropriate tests

30. Ethical considerations
Are data collection techniques likely to cause physical or emotional harm?
Obtain informed consent
Permission to conduct a study