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PUBH202 – ASSESSMENT TASK

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PUBH202 – ASSESSMENT TASK 2 General instructions and dataset guide This assessment task uses the Longitudinal Survey of ACU Student Health and Wellbeing, a (fictional) cohort study involving a survey administered to students on enrolment with ACU (first year baseline) and selected follow up data (during third year). For this task, you are presented with baseline data, along with selected follow-up data (where indicated) on: Road traffic accidents Please note that it is not sufficient to copy and paste tables in the SPSS format from SPSS output files into your Word file. The table...

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PUBH202 – ASSESSMENT TASK 2 General instructions and dataset guide This assessment task uses the Longitudinal Survey of ACU Student Health and Wellbeing, a (fictional) cohort study involving a survey administered to students on enrolment with ACU (first year baseline) and selected follow up data (during third year). For this task, you are presented with baseline data, along with selected follow-up data (where indicated) on: Road traffic accidents Please note that it is not sufficient to copy and paste tables in the SPSS format from SPSS output files into your Word file. The tables need to be in a format suitable for publication and you are asked to use APA format for the tables (no vertical lines). So you could either copy and paste tables from SPSS and edit them in Word to bring them into APA format and you would delete all the cells that are not needed, or you would create a new table in Word in which you paste the necessary cells. You may need to look at example papers for this task (to assist with the best presentation of your data). See Turner & McClure 2003 (available via LEO in the section on “Assessment task 2”), as well as others shown as examples during lectures. However, unlike in other assignments, you do not need to provide references and a list of references. For percentages one decimal point is sufficient, for means and standard deviations please provide two decimal points and for odds ratios and confidence intervals three decimal points. Please refer to the Resources page on LEO for SPSS instructional videos and formatting and other requirements for reporting of statistical results. Due date: Friday, 18 th May 2018, 5pm (week 11) Weighting: 30% Assistance No direct assistance with specific questions or techniques can be provided by the Lecturer or Tutor. If students have general questions (e.g. how to submit) or require clarification on any details about variables (listed below), please e-mail (klaus.gebel@acu.edu.au). In preparing for this assessment task, you should review all tutorial materials, SPSS lectures and the instructional videos provided via LEO throughout the course. All instructional videos have been consolidated on LEO into a specific page in the “Resources” section. Submission When completed, please upload the following three files onto LEO: 2 1. A .doc or .docx file containing your answers, interpretations, tables etc. You should limit direct ‘cut and paste’ from SPSS, tables of results should be edited to contain only the required information. Ensure you also provide interpretation when required. Save your word file with the following file name DSXX_SXXXXXXX.doc – replace the XX with appropriate numbers – DSXX is your dataset allocation – SXXXXXXXX is your student number. So if your data set was DS01, and your student number is S123456, then your file would be called DS01_S123456.doc – this is then uploaded to LEO. 2. Your amended SPSS dataset (.sav file, containing recoding and any other changes) 3. Your SPSS output file (an edited version of the .spv file with all mistakes/practice attempts deleted) Datasets All students have been provided with a different dataset, and so answers will vary for each student. Each dataset contains all variables required; please check the information below about which variables relate to what option. Assessment task Please provide answers to all of the following six questions: 1. In your SPSS file, age (at time of enrolment) is given as a continuous variable. a. Please check the age variable for outliers. If you find students that are younger than 16 or older than 80 then please delete those values (do not delete the whole participant) and report how many outliers you found and what their value for age was. What are your initial thoughts on the distribution of age? Is the distribution sensible? If not, what will you do? (HINT: Do this before continuing on with the rest of the task). What are the mean and standard deviation and the minimum and maximum values for age? b. Describe the distribution of age. Which is the best summary measure to use for age? c. Recode “age” into a new variable (named “age_category”) using the guide from the table below and adding the words from the Description column as value labels for your categorical age variable: New value Description 0 18 years or younger 1 19 to 21 2 22 to 25 3 26 or older What is the frequency (% and number) of students in each of these new age categories? Produce a table, suitable for publication, to present this data. 2. Create a table that provides descriptive statistics (variables measured at baseline) for ACU students overall (including n and % values, respectively mean and standard deviation, or median and interquartile range, as appropriate). Please provide descriptive statistics for all variables apart from the ‘cohort’ variable and the ‘RTA_twoplus_crashes’ variable. Then, provide a written description (2-3 paragraphs) of your findings that informs the reader about the ACU cohort. 3 3. Perform a statistical test(s) that compares the mean scores for aggression, thrill seeking and risk acceptance scores across the following demographics: a. Gender (male/female) b. Metropolitan background status (metro/non-metro) c. Study mode (fulltime/part-time) d. One or more road traffic accidents in the past 12 months (from follow-up survey; one or more accidents/none) e. Two or more road traffic accidents in the past 12 months (from follow-up survey; two or more accidents/none) Present your results in a table (use Table 1 in the Turner et al. paper as a guide - Note: report standard deviations in place of 95% CIs) Provide a brief interpretation of your findings. 4. Using “RTA_one_crash” as the dependent variable, perform a binary logistic regression using the following predictor variables (potential confounders) relating to the RTA study: Type Variables Demographic Age (using newly-created categorical variable and the youngest age group as the reference category) Gender Living arrangements (enter as categorical variable) Domestic/international status Driving Driving distance (average per week) Behaviour Aggression Thrill-seeking Risk acceptance a. Provide a table of odds ratios, confidence intervals and significance values for each predictor variable. For categorical predictor variables please list all categories and mark one of them as the reference category. For question four you just need to provide the table with all the information, but no text that describes your findings. 5. After adjusting for potential confounders, how do living arrangements impact upon road traffic accidents? (Data contained in the table produced in 4a is sufficient to answer this question with a few lines of text). 6. Provide a preliminary interpretation and conclusion about the influence of the ‘driving behaviour’ predictor variables on road traffic accidents (i.e. what is the effect of changes (increase or decrease) in “driver aggression”, “Thrill seeking” and “Risk acceptance” on the odds of experiencing a road traffic accident?)

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1. Distribution 
From the table below, it can be determined that there is no student who is younger than 16 but there is one student who is older than 80 years (191 years). It means there is only 1 outlier and its value for age was 191. 
age    Frequency
Younger than 16    0
16-80    34989
Older than 80    1

As this data is related to age of students as there should be a normal distribution for the age of students. But the figure below shows that the distribution is not sensible (Klein and Verhulst, 2017). It is because there are outliers that show the deviation from the mean of the data set of students’ age. 
 

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