How to prepare a thesis

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How to prepare a thesis

  1. 1. GUIDELINES FOR PREPARATION OF DISSERTATION/THESIS Dr. Gopalrao Jogdand, M.D. PhD. (U.S.A.) Professor & Head, Department of Community Medicine.
  2. 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. 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. 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. 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. 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. 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. 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. 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. 10. Sampling strategies  Why sample size?  For addressing the research question scientifically and for avoiding certain biases and fallacies.  Chance bias.  Statistical fallacies.
  11. 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. 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. 13. Sampling error: The difference between population parameter and sample statistics
  14. 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. 15. Sampling Procedures ‡ Non-probability Samples: # Incidental # Quota # Purposive
  16. 16. ‡ Multi Phase Sampling: ‡ Sequential Sampling (Quality control): ‡ Panel Sampling: Probability Samples
  17. 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. 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. 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. 20. Ø Collect basic data from large sample Ø Collect details from sub sample. Multiphase Sampling
  21. 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. 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. 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. 24.  Design of the study: * estimating average or proportion * Difference between two averages or proportions Pre-requisites
  25. 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. 26. Sampling Error Sampling Non-Sampling Errors Coverage Type of controls Processing errors Observational errors
  27. 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. 28. Less tolerable error = more the sample size: Error
  29. 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. 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. 31.  Statistical Software. How to get a sample size ?
  32. 32. Thank You

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