Ratio de endeudamiento

As explained in section 3.3.2.2, the self-reported frequency of speeding variable measured the frequency of speeding at two levels: exceeding the posted speed limit by ‘up to 10 kilometres per hour’ and ’10 kilometres per hour or more ’.

Table 4.3 reports the mean and standard deviation for each item. Appendix D provides further information regarding the distribution of responses and percentages for the speeding dependent variables.

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It was found that participants reported exceeding the posted speed limit more frequently by up to 10 kilometres per hour than by 10 kilometres or more per hour.

The relationship between the speeding non-compliance low and non-compliance high constructs was also explored. It was found that there was a significant positive relationship between exceeding the posted speed limit by up to 10 kilometres per hour and 10 kilometres or more per hour (r = .60; p < .001). This suggests that those who infrequently engage in low-range speeding (i.e., up to 10 kilometres per hour) are also likely to infrequently engage in high-range speeding (i.e., 10 kilometre per hour or more); and those who frequently engage in low-range speeding are more likely to frequently engage in high-range speeding.

Table 4.3

Descriptive statistics for self-reported speeding items

Speeding Variable M (SD) Significance level

Self-reported frequency of speeding: Non-compliance low

4.23 (1.69) t = 27.31, p < .001

Self-reported frequency of speeding: Non-compliance high

2.50 (1.58)

Figure 4.2 shows the pattern of responding to the non-compliance low, and non-compliance high speeding variables. For the non-compliance low question, the pattern of responding was spread reasonably evenly across the seven point scale.

Only 3.1% (n = 17) of the sample indicated that they “never” exceeded the posted speed limit by up to 10 kilometres per hour. In the case of the non-compliance high question, approximately 31.7% (n=173) of the sample indicated that they never drove 10 kilometres per hour or more above the posted speed limit. It was observed that this variable was positively skewed, however given that this item represents more

deviant speeding behaviour it is expected that participants would report lower frequencies. The pattern of responses for both questions across the non

low and non-compliance high items suggest that most of the participants exceed the posted speed limit at least some of the time.

Figure 4.2. Comparison of participants self posted speed limit (N = 54

For the purpose of multivariate analyses, a composite variable was created that represented a global measure of the frequency of speeding. The two non

questions provide the means of differentiating between those who are willing to engage in more

high-global frequency of self

participant responses and dividing their overall score by the number of items. Thus the response scale ranges from one to

the speed limit more frequently. As noted in section 3.3.2.2, this method is similar to the technique employed in the research conducted by Fleiter and Watson

Fleiter (2010). This variable had a mean of 3.36 (

The drink driving dependent variable was designed to measure the participant’s .0

deviant speeding behaviour it is expected that participants would report lower frequencies. The pattern of responses for both questions across the non

compliance high items suggest that most of the participants exceed the posted speed limit at least some of the time.

Comparison of participants self-reported frequency of exceedin posted speed limit (N = 546).

rpose of multivariate analyses, a composite variable was created that represented a global measure of the frequency of speeding. The two non

questions provide the means of differentiating between those who are willing to -range speeding behaviour and those who are not. Therefore, a global frequency of self-reported speeding variable was created by summing

participant responses and dividing their overall score by the number of items. Thus the response scale ranges from one to seven with higher scores reflecting exceeding the speed limit more frequently. As noted in section 3.3.2.2, this method is similar to the technique employed in the research conducted by Fleiter and Watson

Fleiter (2010). This variable had a mean of 3.36 (SD = 1.46).

The drink driving dependent variable was designed to measure the participant’s Self-reported frequency of speeding

Speeding Non compliance Low Speeding Non compliance High

deviant speeding behaviour it is expected that participants would report lower frequencies. The pattern of responses for both questions across the non-compliance

compliance high items suggest that most of the participants exceed the

reported frequency of exceeding the

rpose of multivariate analyses, a composite variable was created that represented a global measure of the frequency of speeding. The two non-compliance questions provide the means of differentiating between those who are willing to

ge speeding behaviour and those who are not. Therefore, a variable was created by summing

participant responses and dividing their overall score by the number of items. Thus seven with higher scores reflecting exceeding the speed limit more frequently. As noted in section 3.3.2.2, this method is similar to the technique employed in the research conducted by Fleiter and Watson (2006) and

The drink driving dependent variable was designed to measure the participant’s

Speeding Non-compliance Low Speeding Non-compliance High

level of compliance with drink driving legislation in Australia. Participants were asked: “In the past 6 months, how often did you drive after drinking alcohol but may have been over the legal BAC limit for your licence type?” This variable had a mean of 1.6 (SD = 1.31). Examination of the distribution revealed a significant positive skew (see figure 4.3). Square root and logarithmic transformations were performed in an attempt to reduce the impact of skewness; however neither transformation technique was able to resolve this issue. Appendix D provides further information regarding the distribution of responses and percentages for the drink driving dependent variable.

It was observed that 71.2 percent (n = 389) of participants responded that they

‘never’ drove after drinking alcohol while they may have been over the legal BAC limit for their licence type. Thus, 27.3 percent (n = 149) of the sample responded between two and seven on the Likert scale where one equals never and seven most occasions⁹. This suggests that at some point during the past six months, these participants had driven at some point when they may have been over the legal BAC limit for their licence type.

9 Please note that 1.5% of the sample did not respond to this question.

Figure 4.3. Frequency that participants drove when they may have been over the legal BAC limit for their licence type (N = 546

For the bivariate analyses, the skewed nature of the drink driving dependent variable prompted the use of non

the purposes of the regression analyses it was necessary to dichotomise the variable by dividing the participants into two groups. Group one was labelled

drivers’ and participants who responded ‘neve 389). Group two were labelled

who responded from two to seven on the s

latter group represented those drivers who indicated they

during the past six months when they may have been over the legal BAC limit for their licence type.

In order to check the validity of the drink driving measure and dichotomisation of the distribution of drink driving responses, an

self-reported drink driving convictions of those who were categorised as a drink driver or not. The results found that these two groups differed significantly on their

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requency that participants drove when they may have been over the for their licence type (N = 546).

For the bivariate analyses, the skewed nature of the drink driving dependent variable prompted the use of non-parametric measures of association. However, for the purposes of the regression analyses it was necessary to dichotomise the variable by dividing the participants into two groups. Group one was labelled

and participants who responded ‘never’ were assigned to this group (n = ). Group two were labelled ‘Drink drivers’, and comprised those participants who responded from two to seven on the seven-point Likert scale (n = 149

latter group represented those drivers who indicated they had driven at some point during the past six months when they may have been over the legal BAC limit for

In order to check the validity of the drink driving measure and dichotomisation of the distribution of drink driving responses, an analysis was undertaken to examine

reported drink driving convictions of those who were categorised as a drink driver or not. The results found that these two groups differed significantly on their

Self-reported frequency of drink driving

requency that participants drove when they may have been over the

For the bivariate analyses, the skewed nature of the drink driving dependent etric measures of association. However, for the purposes of the regression analyses it was necessary to dichotomise the variable by dividing the participants into two groups. Group one was labelled ‘Non-drink

assigned to this group (n = , and comprised those participants

point Likert scale (n = 149). This had driven at some point during the past six months when they may have been over the legal BAC limit for

In order to check the validity of the drink driving measure and dichotomisation analysis was undertaken to examine reported drink driving convictions of those who were categorised as a drink driver or not. The results found that these two groups differed significantly on their

reported frequency of drink driving

drink driving convictions, with 57.1% of those who had been convicted being categorised as a drink driver compared with 42.9% who were classified as non-drinkers; χ² (1) = 9.89 p = .02 compared to 42.9% of those categorised as non-drink drivers.