1. Why concepts of statistics are important in public health research with respect to the research cycle? Give your answer writing with adequate explanation. (10 marks)
2. A UK study of factors affecting the outcome of pregnancy among 1513 women reported that the overall incidence of pre-term births was 7.5%, SE = 0.68%, 95% CI 6.1 to 8.8% (Peacock et al. 1995).
a. What is meant by SE = 0.68%? (3 marks)
b. What is meant by 95% CI 6.1 to 8.8%? (3 marks)
c. What two distributions are used to calculate the SE and the CI? (3 marks)
d. How would the confidence interval change if 90% limits were used? (3 marks)
e. How would the confidence interval change if 99% limits were used? (3 marks)
f. Another study conducted at about the same time in Denmark and including 51851 women, reported that the overall incidence of pre-term birth was 4.5% (95% CI 4.3 to 4.7%). Explain why this 95% CI is narrower than that reported in the UK study. Do you think that there is a real difference in pre-term birth rates between the two populations being studied? (5 marks)
3. In a baseline survey, the prevalence of full immunization among 12 – 23 months of children was found to be 45 per cent. After three years of a special project, the end line survey estimated prevalence of full immunization as 48 per cent. Can we say that prevalence of full immunization has increased during this period? Give your answer writing with adequate explanation. (No computation are needed). (10 marks)
4. Can we interpret results of hypothesis testing based on P value only or we should also consider Confidence Interval and value of test statistics? Illustrate your answer by giving suitable example. (10 marks)
5. The following table shows the serum cholesterol concentrations of 20 smokers and 20 non-smokers, matched for age and sex, recruited for a study of glucose response. Statistical analysis was by two-tailed, unpaired Student’s t test (Facchini et al. 1992).
Cholesterol concentration, mean (SEM) in mmol/L
|
|
Smokers |
Non-smokers |
t test |
|
Total plasma |
4.49 (0.19) |
4.48 (0.17) |
NS (Non-significant) |
|
Very low density lipoprotein (VLDL) |
0.45 (0.06) |
0.23 (0.04) |
P < 0.005 |
|
Intermediate density lipoprotein (IDL) |
0.18 (0.03) |
0.22 (0.04) |
NS |
|
Low density lipoprotein (LDL) |
2.72 (0.17) |
2.53 (0.13) |
NS |
|
High density lipoprotein (HDL) |
1.16 (0.05) |
1.51 (0.08) |
P < 0.005 |
i. What is meant by a ‘two-tailed, unpaired Student’s t test’?(2 marks)
ii. What conditions must the data satisfy for these t tests to be valid? Are these likely to be satisfied here?(2 marks)
iii What extra information could be given in the table? (2 marks)
iv. What aspect of the data has been ignored in the analysis?(4 marks)
6a. The birthweights of 1333 fifty-year-old Swedish men were traced through birth records. Adult height and birthweight were significantly correlated (r = 0.22, P < 0.001) (Leon et al. 1996).
i. What is meant by ‘correlated’ and ‘r = 0.22’? (2 marks)
ii. What assumptions are required for the calculation of the P value? (2 marks)
iii.What can we conclude about the relationship between adult height and birthweight?(2 marks)
6b. A general practice based study sought to find out if people’s ears increase in size as they get older. Two hundred and six patients were studied with ear size being assessed by the length of the left external ear from the top to the lowest part. Measurements were made simply, using a transparent plastic ruler. The relation between the patient’s age and ear length (see graph below) was examined by calculating a regression equation.
Mean age of patient was 53.75 years (range 30-93) and mean ear length was 67.5 mm (range 52-84 mm). The linear regression equation was “Ear length = 55.9 + 0.22 x age” with 95% CI for the b coefficient being 0.17 to 0.27. The author concluded that ‘It seems therefore that as we get older our ears get bigger (on average by 0.22 mm a year)’ (Healthcote 1995).
i. Is the distribution of ear size skew or symmetrical and why? (1 mark)
ii. Is the distribution of age skew or symmetrical and why? (1 mark)
iii.What are the interpretations of the numbers 55.9 and 0.22 in the regression equation?(2 marks)
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