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PUBH620 Biostatistics Assignment - MJA manuscript, Australian Catholic University, Australia

Learning Outcomes -

• Distinguish between different statistical tests, especially in terms of application and interpretation.
• Develop a sound statistical approach to the analysis and interpretation of public health data and communicate findings in an academic-standard output.
• Critique public health research on the basis of its statistical methods, analysis and interpretation.

Purpose - The major purpose of this assessment task is to consolidate the various aspects of this course (critical appraisal of research, statistical methods) in a way that represents something useful for you in your later careers.

Assessment Task - MJA manuscript: Present your results for your chosen option (OPTION 1 ROAD TRAFFIC ACCIDENTS OR OPTION 2 DEPRESSION AND OBESITY) in the format of a manuscript suitable for submission to the Medical Journal of Australia.

Answer - Medical Journal of Australia Manuscript

Title - Stastical survey on road traffic accident in Australia

Abstract

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Introduction

Methodology

The survey method was adopted for the questioning among students of various gender, the metropolitan in the state . The results were analysed in the ANOVA and regression, standard deviation methods were adopted to record the analysis. The performance in the survey is discussed in the following results for road safety awareness (Susan Gargett, Luke B Connelly,Son Nghie, 2011).

Results and discussion

a. The road safety dataset indicates the following values

 N Minimum Maximum Mean Std. Deviation AGE 38681 16 59 20.50 4.888 Valid N 38681

The mean age of the participant is 21 with the standard deviation ±4.88 S.D. The minimum and maximum age of the participant is 16 and 59 respectively.

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b. Frequency of Age category

 AGE_CATEG Frequency Percent Valid Percent Cumulative Percent Valid Age 18 11879 30.7 36.2 36.2 Age 19-21 11672 30.2 35.6 71.8 Age 22-25 5494 14.2 16.8 88.6 Age 26 and above 3755 9.7 11.4 100.0 Total 32800 84.8 100.0 Missing System 5881 15.2 Total 38681 100.0

The frequency table portrays that total students aged 18 during enrolment (30.7%) which is higher than rest other age category. (30.2%) Students aged 19-21 participated in this survey. Only 15% of student aged less than 18 participated in this survey. Students aged 22-25 accounted for only 14.2%. Finally, only 9.7% students aged 26 and < contributed to this study.

The mean and standard deviation values were depicted below

 Mean S.D N Cohort 5.0695 2.25016 38681 State 1.8736 .87565 38681 Age 20.50 4.888 38681 Gender .7299 .44403 38681 Living Arrangement .7454 .87069 38681 Faculty 2.2809 1.02867 38681 Degree Type .1050 .30654 38681 Metro .1556 .36244 38681 Study Mode .1011 .30148 38681 Fee Status .1666 .37259 38681

The frequency percentage values were calculated for all variables individually and depicted below.

 Cohort Frequency Percent Valid 2005.00 3259 8.4 2006.00 3615 9.3 2007.00 3944 10.2 2008.00 4086 10.6 2009.00 5010 13.0 2010.00 5687 14.7 2011.00 6383 16.5 2012.00 6697 17.3 Total 38681 100.0

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 State Frequency Percent Valid NSW 15860 41.0 Victoria 13571 35.1 Queensland 7528 19.5 ACT 1722 4.5 Total 38681 100.0

 Age category Frequency Percent Valid Age 18 11879 30.7 Age 19-21 11672 30.2 Age 22-25 5494 14.2 Age 26 and above 3755 9.7 Total 32800 84.8 Missing System 5881 15.2 Total 38681 100.0

 Gender Frequency Percent Valid Male 10449 27.0 Female 28232 73.0 Total 38681 100.0

 Living Arrangement Frequency Percent Valid At home 20840 53.9 College/student accom 6850 17.7 Independently 10991 28.4 Total 38681 100.0

 Faculty Frequency Percent Valid Arts and Sciences 9004 23.3 Education 15038 38.9 Health Sciences 11729 30.3 Theology and Philosophy 588 1.5 Business 2322 6.0 Total 38681 100.0

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 Degree Type Frequency Percent Valid Single 34620 89.5 Double 4061 10.5 Total 38681 100.0

 Metro Frequency Percent Valid Metro 27223 70.4 Non-metro 5015 13.0 Total 32238 83.3 Missing System 6443 16.7 Total 38681 100.0

 Study Mode Frequency Percent Valid FT 34770 89.9 PT 3911 10.1 Total 38681 100.0

 Fee Status Frequency Percent Valid Domestic 32238 83.3 International 6443 16.7 Total 38681 100.0

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Q3.

a. Gender

The demographical differences on road behaviour scores were observed using One Way ANOVA method.

H0: There is no gender bias in road behaviour scores such as in aggression, thrill seeking and risk acceptance

H1: Male drivers exhibit high Road behaviour scores than female

One way ANOVA was performed to assess the gender differences in aggression, thrill seeking and risk acceptance scores.

 ANOVA Sum of Squares Df Mean Square F Sig. driver_agg Between Groups .131 1 .131 .007 .934 Within Groups 729828.133 38679 18.869 Total 729828.264 38680 thrill Between Groups .205 1 .205 .137 .711 Within Groups 57918.686 38679 1.497 Total 57918.891 38680 risk_accep Between Groups 46.862 1 46.862 2.468 .116 Within Groups 734310.930 38679 18.985 Total 734357.792 38680

The table reported the gender differences between the groups for aggression, thrill seeking and risk acceptance scores, F(38680) = 0.07, alpha = 0.93>p = 0.005 at 95% C.I, F(38680) = 0.137, alpha = 0.711>p = 0.005, at 95% C.I., F(38680) = 2.468, alpha = 0.116>p = 0.005 at 95% C.I. respectively. Hence, null hypothesis is accepted.

b. Metropolitan Background status

H0: There is no metropolitan background status variations observed in road behaviour scores such as in aggression, thrill seeking and risk acceptance

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H1: Road behaviour scores differs with metropolitan background status of the subjects

 ANOVA Sum of Squares df Mean Square F Sig. driver_agg Between Groups 9.590 1 9.590 .510 .475 Within Groups 606728.539 32236 18.821 Total 606738.129 32237 Thrill Between Groups .702 1 .702 .470 .493 Within Groups 48122.464 32236 1.493 Total 48123.166 32237 risk_accep Between Groups 14.203 1 14.203 .751 .386 Within Groups 609980.093 32236 18.922 Total 609994.295 32237

The ANOVA table reported the mean metropolitan background status differences between the groups for aggression, Thrill seeking behaviour scores and risk acceptance scores F(38680) = 0.510, alpha = 0.475>p = 0.005 at 95% C.I., F(38680) = 0.470, alpha = 0.493>p = 0.005, at 95% C.I. risk acceptance scores, F(38680) = 0.751, alpha = 0.386>p = 0.005 at 95% C.I. respectively. Hence, null hypothesis is accepted and concluded that there is no statistical significant mean metropolitan background status differences in mean aggression, thrill seeking and risk acceptance scores

c. Study Mode

 ANOVA Sum of Squares df Mean Square F Sig. driver_agg Between Groups (Combined) 1.805 1 1.805 .096 .757 Linear Term Unweighted 1.805 1 1.805 .096 .757 Weighted 1.805 1 1.805 .096 .757 Within Groups 729826.459 38679 18.869 Total 729828.264 38680 Thrill Between Groups (Combined) .026 1 .026 .017 .895 Linear Term Unweighted .026 1 .026 .017 .895 Weighted .026 1 .026 .017 .895 Within Groups 57918.865 38679 1.497 Total 57918.891 38680 risk_accep Between Groups (Combined) 97.748 1 97.748 5.149 .023 Linear Term Unweighted 97.748 1 97.748 5.149 .023 Weighted 97.748 1 97.748 5.149 .023 Within Groups 734260.044 38679 18.983 Total 734357.792 38680

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H0: There is no differences in road behaviour scores such as in aggression, thrill seeking and risk acceptance based on student's study mode

H1: Road behaviour scores differs with study mode of the subjects

The ANOVA table clearly reported that lack of mean variations in study mode groups on driving road behaviour scores such as aggression, thrill seeking behaviourand risk acceptance scoresF(38680) = 0.96, alpha = 0.757>p = 0.005 at 95% C.I. F(38680) = 0.170, alpha = 0.895>p = 0.005, at 95% C.I., F(38680) = 0.751, alpha = 5.14>p = 0.023 at 95% C.I. Hence, null hypothesis is accepted and concluded as that there is no statistical significant mean study mode status differences in mean aggression, thrill seeking and risk acceptance scores

d. RTA in past 12 months

 ANOVA Sum of Squares df Mean Square F Sig. driver_agg Between Groups (Combined) 135397.559 1 135397.559 8810.181 .000 Linear Term Unweighted 135397.559 1 135397.559 8810.181 .000 Weighted 135397.559 1 135397.559 8810.181 .000 Within Groups 594430.705 38679 15.368 Total 729828.264 38680 Thrill Between Groups (Combined) 10410.295 1 10410.295 8475.515 .000 Linear Term Unweighted 10410.295 1 10410.295 8475.515 .000 Weighted 10410.295 1 10410.295 8475.515 .000 Within Groups 47508.595 38679 1.228 Total 57918.891 38680 risk_accep Between Groups (Combined) 100151.284 1 100151.284 6108.029 .000 Linear Term Unweighted 100151.284 1 100151.284 6108.029 .000 Weighted 100151.284 1 100151.284 6108.029 .000 Within Groups 634206.508 38679 16.397 Total 734357.792 38680

H0: There is no differences in road behaviour scores such as in aggression, thrill seeking and risk acceptance based on RTA occurred in past 12 months

H1: Road behaviour scores differs with study mode of the subject

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The ANOVA table reported the no differences in mean RTA in past 12 months status between the groups for aggression F(38680) = 8810, alpha = 0.00<p = 0.005 at 95% C.I. Thrill seeking behaviour scores also reveal the mean RTA in past 12 months status differences since F(38680) = 8475, alpha = 0.00<p = 0.005, at 95% C.I. The table also failed to reveal statistical significant mean study RTA in past 12 months status for risk acceptance scores, F(38680) = 6108 alpha = 0.00<p = 0.005 at 95% C.I. Hence, null hypothesis is accepted and concluded that there is a statistical significant mean RTA in past 12 months status differences in mean aggression, thrill seeking and risk acceptance scores

5. A Binary Logistic regression was performed to estimate the role of age, gender, living arrangements and metropolitan status, behavioral scores such as driving aggression, thrill seeking and risk acceptance as well as driving distance on the RTA for past 12 months

Odds Ratio Table

 Classification Tablea,b Observed Predicted RTA_one_crash Percentage Correct No RTAs One RTA or more Step 0 RTA_one_crash No RTAs 23799 0 100.0 One RTA or more 3546 0 .0 Overall Percentage 87.0 a. Constant is included in the model. b. The cut value is .500

 Variables in the Equation B S.E. Wald Df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a GENDER -.658 .064 106.643 1 .000 .518 .457 .587 LIVING_ARRANGE 6.081 2 .048 LIVING_ARRANGE(1) -.185 .076 5.862 1 .015 .831 .715 .965 LIVING_ARRANGE(2) -.161 .115 1.962 1 .161 .851 .680 1.066 METRO -.025 .089 .081 1 .776 .975 .818 1.162 AGE_CATEGORY -.482 .033 216.491 1 .000 .618 .579 .659 dist_driving -.056 .059 .902 1 .342 .946 .842 1.061 driver_agg .663 .030 503.393 1 .000 1.940 1.831 2.056 thrill .531 .096 30.542 1 .000 1.701 1.409 2.053 risk_accep .631 .012 2770.214 1 .000 1.880 1.836 1.925 Constant -17.530 .411 1816.958 1 .000 .000 a. Variable(s) entered on step 1: driver_agg, thrill, risk_accep.

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Living arrangements

 Categorical Variables Codings Frequency Parameter coding (1) (2) LIVING_ARRANGE At home 17355 1.000 .000 College/student accom 2352 .000 1.000 Independently 7638 .000 .000

Regression equation

The predicted odds of RTA past 12 months = -0.658 (Gender) - 0.185 (Living Arrangement_1) -0.25 (metropolitan status) - 0.482( Age category) - 0.56 (Driving distance) + 0.663 (Aggregation score) + 0.531 (Thrill seeking score) + 0.631 (risk acceptance score) - 17.50

This infers that gender, living arrangement, metropolitan status, age and driving distance have negative linear predictor relationship with RTA. The demographical variable has no impact on the road accidents. Alternately, RTA exhibits positive prediction between the aggressive, thrill seeking and risk acceptance scores. Most of the students exhibit home and independent living arrangement.

Conclusion

The survey depicted the behaviour changes year by year by the students to the road traffic accident and the analysis was conducted for the students revealed a lots of change in road behaviour. The ANOVA regression analysis provided a behavioural analysis gender wise and the concluded that the fatalities gap was less in the recent years.

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