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Assessment for MH900 Epidemiology and Statistics
2024/25
Students should complete both sections
Marks are allocated as follows:
Section 1: Epidemiology 50 marks
Section 2: Statistics
Question 1: 25 marks
Question 2: 25 marks
The pass mark is 50% overall.
Submission date: 11 December 2024 – before 12 noon.
Electronic submission procedure: please submit two files, one for epidemiology and one for statistics.
Extension of submission date
Extensions are not available routinely - if you are not going to be able to hand your assignment in on time it is essential that you make an on-line written request before the submission date, outlining the extenuating circumstances, using the standard on-line extension request form.
Late submission
Assignments not received by the deadline, or by any agreed extension date will be penalised at the rate of 5 marks per day late, in line with University policy.
Section 1: Epidemiology
Prepare a study design to answer a research question within one of the following topic areas - you must formulate an appropriate question.
NOTE: The topics listed are the same as used for group work. Whilst most students chose to build on the topic covered by their group presented during the taught module, you may elect to change topic and tackle one of the other questions or, by prior agreement, your own question. You must design an analytical epidemiological quantitative study – so any research questions must be ones that can be addressed by this approach.
IMPORTANT: Even though this is based on your group work, you MUST NOT directly use material from your presentation. It MUST be paraphrased. Failure to do so will be flagged as collusion and result in referral to the Academic Integrity Committee.
Guidelines
As in the group work guidelines, the study design should address the points listed below. Examiners will use this guideline in assessing work and you will lose marks if you have failed to address any of these points. Your total word limit for this section (Epidemiology) is 2000 words (+/- 10%, so 1800 to 2200 words). Tables and references are excluded from the word count. If you need to use appendices, these should be used for supplementary non-essential text only; examiners will not mark these.
The following headings may help in preparing your work: Research Question, Background, Study Design, PICO/PECO and Eligibility Criteria, Sampling and Sample Size, Data Collection, Data Analysis, Limitations (e.g. bias, confounding), Ethical and Data Management Issues.
NOTE: this is a study design only; no “Results” or “Discussion” of anticipated results sections are needed. The data analysis will be the data analysis plan, explaining how you would analyse the data. You should explain your thinking more than you would if writing a study protocol normally, justifying your choice of study design and other decisions that you have made such as the effect size used in sample size calculations.
Main issues to be addressed
1 The study must have a quantitative methodology using an established study design, or an innovative variation on standard designs.
2 Background to the research question can be described briefly but should include a general introduction to the subject area and focus on the specific background that would lead to you posing the research question and planning the study that your report proposes.
3 Research question(s) and / or any hypotheses must be stated clearly.
4 The type of study design proposed should be identified clearly and the rationale for its choice presented. This should demonstrate your understanding of study design purposes and limitations. You may choose to say why you did not choose a particular design as part of justifying your final choice.
5 Some consideration of population and study sample is essential: this should include patients or other participants, how the sample will be selected and the study setting.
6 A detailed description of methods could include whichever of the following are relevant:
· Outcome(s) of interest
· Exposure(s) or interventions
· Statistical analyses - types of data to be collected, and your plan for data
analysis, including the planned use of statistical testing (e.g. what tests you would use)
· Randomisation if relevant
· Bias and confounding and steps that can be taken to consider and minimise
them - your report should discuss possible sources of bias and confounding in the study design and steps to be taken to minimise their effects. If your design avoids either or both of these problems that should be explained.
· Practical aspects of the proposed research methods, including data collection
· Ethical issues
Topics for group work / assignment
The effects of environment on mood or exercise
Does where you live affect your mood, or how active you are? Design a study to describe the effect of your local environment on depression or on physical activity.
Section 2: Statistics
Guidelines for students
In estimating statistics and conducting tests you may use appropriate computer applications, but include computer outputs that contain the values that you use to answer the questions. Graphics or figures, if you make any, should be produced using a computer. Where hand drawn graphics are to be submitted, these should be scanned and appended to your work.
Answer BOTH of the following questions.
Question A (25 marks)
Data analysis exercise
Data have been collected in a randomised controlled trial on the effectiveness of a new method for providing oxygen support for patients with severe community acquired pneumonia (CAP). Patients over 65 years of age considered to be in need of oxygen support were randomised to either receive the standard or new approach. In all other respects patients in both groups received standard care. All patients were followed up until they were discharged from hospital or died. The primary outcome was whether or not a patient’s condition deteriorated to the extent that they had to be admitted to an intensive care unit (ICU) within 28 days.
A total of 410 patients were recruited to the trial, with 210 and 200 randomised to receive each of the new and standard interventions respectively. Among patients receiving the standard intervention, there were 56 ICU admissions, while the number of ICU admissions among the patients receiving the new intervention was 45. The outcome was observed for all patients and no patients died prior to being admitted to ICU.
Additional historical data were available from 100 patients who received the standard intervention treatment when it was introduced ten years ago. Of these patients, 33 were admitted to ICU within 28 days.
(a) The main question of interest is whether the new intervention leads to a reduction in ICU admission rates relative to the standard intervention.
(i) Explain, giving your reasoning, which of the data given above you would use to answer this question. Express these data in the form of a table, including totals and percentages that are helpful in interpretation of the data. (3 marks)
(ii) Based on the data that you presented in your answer to (i) conduct an appropriate statistical test to determine whether there is a statistically significantly difference between the numbers of patients being admitted to ICU with the two interventions. State what you conclude from the results of this test. State a condition for the test to be a valid and explain whether or not you think this is reasonable in this case. (4 marks)
(iii) Based on the results you presented in you answer to (i), obtain an estimate of a measure of the difference in proportions of patients admitted to ICU within 28 days together with a 95% confidence interval. Explain the meaning of this confidence interval and how it relates to the test that you conducted in (ii). (6 marks)
(b) A second question of interest is whether recovery rates for patients receiving the standard intervention have changed over the last ten years. In an attempt to answer this question the researchers have compared data on total length of stay in hospital for patients receiving the standard treatment in the trial described above with that for the group of patients treated ten years ago.
As the distribution of length of hospital stay is known to be skewed, the analysis used the (natural) logarithm of the length of stay in days for each patient. The researchers plotted the log-transformed values against the date of the start of treatment. The plot is given in Figure 1. They have also used SPSS to fit a linear regression model relating these with the date of the start of treatment converted to the number of days since 1 Jan 2012. Part of the SPSS output from this analysis is given in Table 1.
(i) Explain what model is being fitted in the analysis given in Table 1. (1 mark)
(ii) State two assumptions required for the hypothesis test presented to be valid and explain, giving your reasons, whether or not you believe these are likely to be reasonable in this case. (4 marks)
(iii) Give the meaning of the most important figures presented in Table 1. Using these results, explain whether the data suggest that there has been a change in length of hospital stay over the ten year period. (4 marks)
(iv) Give two reasons why the data shown in Figure 1 might not fully answer the research question of whether recovery rates for the standard treatment have changed over the last ten years. (3 marks)