1. GUIDELINES FOR PREPARATION OF
DISSERTATION/THESIS
Dr. Gopalrao Jogdand, M.D. PhD. (U.S.A.)
Professor & Head,
Department of Community Medicine.

2. Dissertation
 Why a dissertation?
 Just for fulfilling the requirement for a
doctoral degree program.
 For learning how to conduct medical research
scientifically.
 Basic requirement for starting career as a
researcher.

3. Types of research
 Quantitative research:
 Aim is to measure certain variables.
 Estimation of population parameters.
 Statistical testing of hypothesis.
 Qualitative research:
 Mainly concerned with obtaining information
about certain population characteristics such as
socio- economic status, concepts about health,
health seeking behaviour, utilization of health
services.

4. Selecting a research topic
 After rigorous scanning of medical literature,
studying relevant material from the internet
or guidance from the guide/Supervisor.
 A blue print of the research topic is formed in
the mind of a postgraduate student.
 This idea can be further crystallized by
collecting references from various sources.
 Avoid duplication or collection of trash
references.

5. Planning
 Administrative feasibility:Check for available research
facilities in your institution or the collaborating agency.
 Procure administrative clearance from the ethical
committee.
 Procure permission from the agency where the study has to
be conducted.
 Procure Informed consent of study participants/patients.
 Operational feasibility in field based research
studies/community based studies assess the participation
and co-operation of the study population and the resources
required.
 Financial feasibility.

6. Scanning the medical literature
 Collection and review of relevant literature.
 Searching for cumulative index medicus in
the library.
 Index medicus is available in two forms:
a. Author index.
b. Subject index.
 Collecting references from National and
International journals.

7. Resources on the net
 List of some Important Internet websites:-
 1. http://www.isoc.net
 2. http://www.medlineplus.gov
 3. http://www.clinicaltrials.gov
 4. http://www.hon.ch
 5. http://www.nlm.nih.gov
 6. http://www.biosis.org
 7. http://www.sis.nim.nih.gov
 8. http://www.healthnet.org.za
 9. http://www.pubmedcentral.nih.gov
 10. http://www.reliefweb.int
 11. http://www.nic.in
 12. http://www.pubmed.com

8. Selection of a study design
 This will depend on the research question and
the best possible way to address it.
 Descriptive studies: 1. Case report and case
series. 2. correlation studies. Observational
studies 3. cross-sectional surveys.
 Analytical studies: 1. case control studies.
2. Cohort studies. 3. Experimental studies.

9. Preparation of a study protocol
 Research question.
 Rationale and apriori hypothesis on the study.
 Review of literature.
 Aims and objectives.
 Preparation and validation of questionnaire, by pilot
study.
 Material and methods.
 Summarization of data and statistical analysis.
 Appendices.
 Summary.
 Bibliography.

10. Sampling strategies
 Why sample size?
 For addressing the research question
scientifically and for avoiding certain biases
and fallacies.
 Chance bias.
 Statistical fallacies.

11. Basic concepts
Population:
Universe:
Reference populn:
Parent Population:
A group of
individuals in which
the researcher is
interested
The Process or Technique of selecting a sample of appropriate
characteristics and adequate size

12. Sample: Subset of the
population
Sampling Frame: Total elements of the
survey population,
redefined according to
certain specifications
Parameters: Summary Measures
e.g. Averages;
Percentages.
Sample Statistics: Summary measures of
sample

13. Sampling
error:
The difference
between population
parameter and
sample statistics

14. Basic Requirements of a Reliable Sample
‡ Efficiency: ability to yield desired information
‡ Representativeness: Similarity to reference
population.
‡ Measurability:valid estimates of variability
‡ Size:adequacy
‡ Coverage:inclusion
‡ Goal Orientation:oriented to research design,

15. Sampling Procedures
‡ Non-probability Samples:
# Incidental
# Quota
# Purposive

16. ‡ Multi Phase Sampling:
‡ Sequential Sampling (Quality control):
‡ Panel Sampling:
Probability Samples

17. Ø All members have equal chance of selection
Ø List all members of population
Ø Random selection: Dice, Coins, Lottery, pages of book
Random tables, calculator,
computer
Random Sampling

18. Ø Stratification of area through maps
Ø Random selection: Dice, Coins, Lottery, pages of book
Random tables, calculator,
computer
Systematic Sampling
Ø First is chosen randomly
Ø Others are chosen systematically
Area Sampling

19. Ø Enumeration of sampling Units
Ø Cumulative counting.
Ø Random selection: First Cluster unit selection
Ø Each cluster 7 units selection by random.
Ø Total 30 clusters. A total of 210 units
Ø Most commonly used method
Cluster Sampling

20. Ø Collect basic data from large sample
Ø Collect details from sub sample.
Multiphase Sampling

21. Ø First select small sample
Ø If questions are not answered, increase the sample size.
Ø Quality control methods in industries utilize this method
Sequential Sampling

22. Ø Randomly select sample.
Ø Collect data at frequent intervals.
Ø Trend has to be studied.
Ø Examples: Sentinel surveillance data; Nutritional
monitoring data; social changes.
Panel Sampling

23.  Sampling Error
 Prevalence of the condition
 Variability between sampling units (SD)
 Desired level of statistical significance (CI)
 Degree of difference/ Strength of Association to
be detected
 - error and  - error
Analytical Method:
Pre-requisites

24.  Design of the study:
* estimating average or proportion
* Difference between two averages or proportions
Pre-requisites

25. Disparity between the true parameter and the
sample statistic:
* Sampling error = 1/n
n = sample size
* Larger the sample, lesser the sample error
Sampling Error

26. Sampling Error
Sampling Non-Sampling
Errors
Coverage
Type of controls
Processing errors
Observational errors

27. If the prevalence of the condition is more; then
sample size will be smaller:
Prevalence
Variability between sampling units (SD)
 Can be known by exploratory/ pilot study
eg.Weight gain in children after dietary
supplementation

28. Less tolerable error = more the sample size:
Error

29.  Consult a statistician
 Refer to tables already available
a. For prevalence studies
b. For comparison groups
 Calculate
a. Prevalence study( mean, proportions)
no = Z2 pq / e2
Z2 = abscissa of the normal curve that cuts
off an area  at the tails
p = prevalence
e = desired level of precision
How to get a sample size ?

30.  In estimating Average or Proportion:
1. Parameter to be estimated
2. Degree of precision (tolerable Sampling error)
3. Desired confidence level
4. Estimated variability (SD)
 significance between proportions/ Means:
1. . Amount of difference of importance
2. Size of  and  error
3. Estimated variability (SD)
How to get a sample size ?

31.  Statistical Software.
How to get a sample size ?

32. Thank You