Q1. A researcher claims that the mean DMFT of males aged 14 to 16 in a particular British city is 5. Explain how you would assess this, writing down the appropriate hypotheses, explaining what statistical test you would apply, how you would summarize the observations and how you would interpret the results of such a test. How would the size of your sample tend to affect the results?
Q2. What do you understand by the following statistical and epidemiological terms? Please give examples where necessary.
a) type I error
b) random sample
c) multiplication law of probability
d) ROC (receiver operating characteristic) curve
e) disease incidence
Q3. You are designing a study to measure periodontal disease in a particular population.
Define and describe inter-examiner variability and intra-examiner variability. What steps would you take to attempt to minimise interexaminer variability in your study. Describe problems that may be encountered when attempting to measure the severity of periodontal disease.
Discuss the characteristics of an ideal dental disease index? Illustrate your answer with reference to well known indices used in dentistry.
Q4. Explain with examples what is meant by null and alternative hypotheses and how they are used in statistical testing? Suppose that you conducted a One-way Analysis of Variance (ANOVA) to compare the maxillary to mandibular tooth-size ratio between 4 ethnic groups and the analysis resulted in a p value of 0.02. What does this really mean and what conclusions would you draw? What further analysis of the same data would yield additional information?
If the initial analysis had resulted in a p value of 0.08, what would that mean and what conclusions would you draw?
Q5. Explain briefly the principles behind, and the use and limitations of three of the following. Suggest situations where they might be used when analysing dental data.
a) Survival analysis
b) 95% confidence interval
c) Sign test
d) Chi-squared test
Q6. Describe the principles behind linear regression. What assumptions are made when linear regression is used? How can linear regression be used for prediction? Give an example of how this method of analysis might be used in dental research.