The aim of this assignment is to test your understanding of the course material and your use of Stata. The assignment will give you an opportunity to put into practice the concepts and methods that you have learned in the course.
It is advisable for you to undertake this assignment after you have studied up to and including Session 9, plus Session 12, of the CAL material. There is no single correct answer to the exercise. However, the tutors marking your assignment will look for an appropriate analysis leading to correct conclusions presented in a format along the lines of that used for a scientific paper (more detailed guidance on this is given below).
The data for this assignment comes from a population-based study of female blood donors in the UK and is in the file named ‘blood.dta’ which can be found in the Assessed Assignment section in Moodle along with these instructions. The data were collected from 1,885 women attending a blood donation centre during 2015. Information on age, smoking, diet (red meat, tea and fruit consumption), iron supplementation and menopause status were collected via questionnaire. Additionally, height and weight were measured by a nurse and used to calculate BMI. In the UK, women must pass a test measuring blood haemoglobin (>125g/dl) before they are allowed to donate blood. In this study, 225 women failed the test and so were not allowed to donate blood on that day, and were instead deferred to return at a later date.
Deferral is an undesirable outcome is known to discourage potential blood donors from returning to donate again. We would like to investigate the impact of menopause on deferral (i.e. not being able to donate blood due to failing the test for blood haemoglobin), and whether this is influenced by iron supplementation. An analysis of this relationship should account for confounders of the association between deferral and menopause status and should include an investigation of whether this association differs by iron supplementation.
Deferral is defined as a binary variable indicating whether a woman donated blood (coded 0) or was deferred due to failing the test for blood haemoglobin (coded 1). Menopause status (also binary) and a number of other factors (including iron supplementation) that may influence donation/deferral are also included in the dataset:
|
Name of variable |
Description |
|
id |
Unique patient identifier |
|
age |
Age in years |
|
bmi |
BMI (kg/m2) |
|
smoke |
Smoking status (0 = never smoker, 1 = ex / current smoker) |
|
redmeatfreq |
Red meat consumption (0 = never, 1 = 0-1 times/week, 2 = 2-3 times/week, 3 = 4-6 times/week, 4 = 7+ times per week) |
|
fruit |
Fruit consumption (0 = never/rarely, 1 = regular consumption) |
|
tea |
Tea consumption (0 = never/rarely, 1 = regular consumption) |
|
menopause |
Menopause indicator (0 = no, 1 = yes) |
|
ironsupp |
Iron supplementation indicator (0 = no, 1 = yes) |
|
deferral |
Deferral indicator (0 = donated blood, 1 = deferred) |
Your AA should answer two research questions:
Does the menopause increase the prevalence of blood donation deferral?
Is the effect of menopause on deferral modified by iron supplementation?
Your aim is to develop a logistic regression model which estimates the effect of the primary exposure on the outcome. In your report, you should assess and discuss to what extent any of these variables act as confounders. Some factors may also potentially modify the effect of menopause on deferral. In this analysis, we are only interested in effect modification by iron supplementation, and you need the only test and report this interaction.
Your report should be structured with sections on Introduction, Methods of Analysis, Results, and Discussion (including conclusions). The majority of the marks are allocated to the Results section which should cover descriptive analysis, model development and assessment of confounding and effect modification. You should aim to use around a quarter of your report describing your analysis strategy, around half on the results and about a quarter discussing your results.
The report should be understandable to people who have not been closely involved in the fieldwork but who are aware of the general aims of the study. Your report should use statistical and epidemiological methods that you have learnt in this module (EPM202) and demonstrate that you have appropriately applied these to the research question and can correctly interpret results. However, you do not need to explain the theoretical concepts behind the epidemiological or statistical methods that you use. The report should describe:
1) how you analysed your data, including the method that you used
2) the results you obtained
3) your interpretation of your results.
Many of the principles involved in writing a good paper for a scientific journal apply to this assignment but:
1) There should be more detailed on the strategy you used to analyse the data than is found in most papers.
2) You should include a very brief introduction including a statement of the research the question, why it is important, the study population, the outcome, the primary exposure and potential confounders. This introduction should be approximately 100 words.
3) You should not cite or discuss relevant literature but you should consider the internal validity of the study (and hence your results).
4) You should discuss the interpretation of your results and how they relate to the research question. This may include alternative statistical explanations for any associations you find.
5) You may assume that the techniques you have used (e.g. chi-squared test, Mantel-Haenszel methods, 95% confidence intervals, likelihood ratio test, etc.) are understood by the reader and do not need explanation, but you do need to say which methods you have used.
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