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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
The road traffic accident fatalities increase in Australia. It recorded 1226 in 2017 this values decrease from 1970 . the value according to stastics in 1970 is 3798.The decrease in the value is due to strict road safety followed in the country . The road death after global fatalities is 17.2 per people deaths is 100000 people. The lower income in smaller prevalence and higher income less fatalities. This paper discusses the road traffic accident survey was conducted in the college among students and the report were generated according to survey. The data set has a three year follow up of the road traffic accident changes and the age group considered in the survey includes the age from 21-59.the survey was conducted based on the awareness of road safety and the result and analysis was discussed in the conclusion part. The discussion predicted that the male drivers exhibit more behaviour than the female drivers. The metropolitan background also centres the road behaviour . The risk was also more in the male than the female in road behaviour. Metropolitan has no scores on the road behaviour as there were proper traffic rules. The ANOVA table was used regression analysis for the survey conducted in the Australian college the gender, metro Politian were considered for the inferences in the results showed a less interference of the road traffic analysis and gender variation were alsaon included in the analysis of the road behaviour (Car Accident Statistics 2019 , 2019). The male responded more than the female for their behaviour toward the road safety.
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Introduction
A survey was conducted among the college students in the Australian catholic university regarding road survey behaviour. The road safety awareness should be introduced in the college for this purpose the survey was taken among the students itself and the result analysis was performed based on the survey answers. the road accident are the main concern globally and the Australia stands the more fatalities and the record shows it has more number of fatalities in the road accident than another countries . Australia is ranked as 14th out of 34 OECD countries for deaths per 100,000 but has since slipped to 17th place as other countries see greater reductions in fatalities each year (Car Accident Statistics 2019 , 2019). In the past 30 years the road accident deaths has dropped in Australia due to more number of awareness created in road behaviour and safety . The largest reduction was found in passenger fatalities 76% was reduced and the pedestrian reduced to 50% in fatalities. In the past few years Australia has seen a 30% increase in cars rate in the road of Australia (Transport in NSW autralia survey, 2019). From 2008 the registration for the cars has increased nearly to 60% in the country and the light weight commercial vehicle s increased to 30% run in roads. The increase in road vehicles has reduced road fatalities recently in Australia (Car Accident Statistics 2019 , 2019). The state wise fatalities are varying as per population in the state. The survey was conducted in this article among the students for a three year survey to analysis the reduction in road fatalities.
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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