Data Analysis and Reporting
FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assignment 1 FMHU5002 Introductory Biostatistics Data Analysis and Reporting Assignment Due Date and Time: Monday, June 3rd 2024 11:59 PM Sydney Time Assignment Category: Submitted Work Assignment Sub-category: Assignment Weighting: 25% Plagiarism and Academic Dishonesty Policy You must complete your assignment alone. Submitting assignments that have been jointly completed is not acceptable. Copying someone else’s work, using generative AI, or quoting from text without adequate attribution of the source is plagiarism and is not acceptable. All assignments will be verified by plagiarism detection software. Serious penalties apply for plagiarism, collusion, or contract cheating. Information about the University’s policy on academic honesty can be found at the following site: https://www.sydney.edu.au/students/academic-integrity.html Late Penalties and Special Consideration Unless you have an approved simple extension, special consideration or an academic plan, 1.25 marks (5% of 25) will be deducted from your assignment mark per day (or part thereof) until Monday, June 12th, 11:59 PM (Sydney Local Time). Assignments submitted past this date without approved special consideration or an academic plan will not be accepted and will be given a zero (0) mark. For students seeking simple extensions or special consideration, please use the following site: https://www.sydney.edu.au/students/special-consideration.html Sydney School of Public Health Semester 1, 2024 FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assignment 2 Submitting your Assessment Submit your assessment as a single file in .docx or .pdf format by 11:59 PM Sydney Local Time on Monday 3rd June 2024 via Canvas (Assessments overview > Assessment 4: Data analysis and reporting assignment > Assignment Submission – Click Here > Select the file to upload and then click “Submit Assignment”). Do not attach a jamovi.omv or a .csv file with your submission. If you have any administrative questions, please post them on the Canvas Discussion Board. Go to Discussions > Data Analysis and Reporting Assignment Discussion. Alternatively contact the Associate Lecturer, Lucy Corbett: [email protected] If you have difficulties submitting the assignment around the due time, please email [email protected] directly with your assignment attached to avoid late penalties. The timestamp of your email will be used as evidence of the date and time of your assignment submission. Please note responses to emails will only occur during business hours on standard working days. Important Notes: • The data for the assignment has been simulated for the purposes of an assessment exercise. As such, the outcomes from these analyses have no practical or clinical meaning. • This assignment paper (including cover page, instructions, and data dictionary) is five (5) pages in length. Please ensure you have all pages. • The variable names and coding of the variables (i.e., the data dictionary) for your dataset are included at the end of this assignment on page 5. • Name your submission file with your student number (SID), unit of study code, and “A4” (e.g., 311275249_FMHU5002_A4.pdf). Ensure all pages are numbered, and that your student number is included in the header or footer of the document. • Assignments are marked anonymously, so please do NOT put your name anywhere on the assignment or submission title. • Any jamovi output presented must be edited to comply with the recommendations for presenting results as covered in the Lecture 1 Notes. Sydney School of Public Health Semester 1, 2024 FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assignment 3 Assignment Questions You have been asked to help analyse the results of a cross-sectional study among males aged 18-65 years old which was undertaken within a local health district to examine the impact of weight status (i.e., overweight / not overweight) on health service usage (i.e., overnight hospitalisation in the past 12 months), and systolic blood pressure (mmHg). Your collaborators within the local health district have provided you with the dataset (in the file “FMHU5002 A4 Dataset.csv”, the data dictionary for which is provided on the last page of this assignment document). The data has already been screened by a colleague, and all values in the dataset should be considered correct (i.e., you do not need to screen the data for impossible, implausible, extreme, or missing values). Question 1 (12 marks) a. Perform an appropriate analysis to assess whether there is an association between weight status and overnight hospitalisations. In your response, clearly state the null hypothesis that is being tested, and provide a brief conclusion including relevant statistical values. Your response should be no longer than 4 sentences. b. Perform an appropriate analysis to determine whether there is an association between weight status and mean systolic blood pressure. In your response, clearly state the null hypothesis that is being tested, and provide a brief conclusion including relevant statistical values. Your response should be no longer than 4 sentences. Question 2 (4 marks) a. For the analysis performed in Question 1a, a prevalence of hospitalisation among people with a weight status of overweight that is 1.4 times that of people not overweight would be considered practically important. Based on your analysis, what can you conclude about the practical importance of the results? b. You are informed that a sample size calculation was performed in the design stage of the study. This calculation determined that, in order to detect a practically important effect with 90% power at the 5% significance level, each study group would require 686 individuals. However, due to staffing and budgetary constraints, this number was not achieved and no further data can be collected. What are the implications of this on the detectable effect and the precision of the estimated effect? Note: you do NOT need to perform any sample size calculations to answer this question. Sydney School of Public Health Semester 1, 2024 FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assignment 4 A colleague has also been analysing the data, and based on input from clinical collaborators, they have included age as a potential confounder of systolic blood pressure in their model, generating the output below: Use the information provided in this output to answer the remaining questions (Question 3 and 4). Question 3 (7 marks) a. Provide an interpretation of the analysis based on the output above. In your response, clearly state the null hypothesis that is being tested, and a brief conclusion including any relevant statistical values. Your response should be no longer than 5 sentences. b. Based on the provided output, what would be the predicted value of systolic blood pressure for an individual who is overweight and is 50 years of age. c. Based on the provided output, what would be the predicted value of systolic blood pressure for an individual who is not overweight and is 50 years of age. Sydney School of Public Health Semester 1, 2024 FMHU5002 Introductory Biostatistics – Data Analysis and Reporting Assignment 5 Question 4 (2 marks) Your colleague has provided you with the following directed acyclic graph (DAG) to help explain why they performed the analysis which produced the output shown above. Assuming this DAG is a true reflection of the relationships between the variables shown, can the regression estimate shown in the above output be interpreted as an estimate of the causal effect of weight status on systolic blood pressure? Making reference to the DAG, explain why / why not? Total = 25 marks This is the end of the assignment questions. The data dictionary for the assessment data set is provided below. Data dictionary Description Identification number Age (years) Weight status Variable Name ID AGEYRS WGHTSTAT Levels (if appropriate) Nominal Continuous, measured in years Dichotomous: – Overweight – Not overweight Overnight hospitalisation in the last 12 months HOSP Dichotomous: – Hospitalised – Not Hospitalised Systolic blood pressure SBP Continuous, measured in mmHg Sydney School of Public Health Semester 1, 2024
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