Monitoring and program evaluation

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					Monitoring and program
evaluation

        Time spent: 9 hrs


         Hossein Naraghi
       CE 590 Special Topics
              Safety
            June 2003
    The need fro monitoring
   Monitoring is systematic collection of
    data about the performance of road
    safety treatments after their
    implementation
       The effectiveness of treatment can be
        assessed
       Post-implementation monitoring is essential
        to ascertain the effects of a treatment
       Improve the accuracy and confidence of
        predictions of that treatment’s effectiveness
        in subsequent applications
        The need fro monitoring
        (continued)
       Monitoring is important to ensure that a
        particular treatment has not led to a significant
        increase in accidents
       The road safety engineer has a duty to ensure
        that the public does not experiencing additional
        hazard as a result of treatments
   The Institution of Highways and
    Transportation defines the purpose of
    monitoring as follow
       Assess the effects of crash occurrence in
        relation to safety objectives
The need fro monitoring
(continued)
   Assess the effects on distribution of traffic
    and speeds of motor vehicle
   Call attention to any unintended effects on
    traffic movement or accident occurrence
   Assess the effect of treatment on the local
    environment
   Find out about the public response to the
    treatment in terms of its acceptability in
    general and people’s concern about safety in
    particular
    The need fro monitoring
    (continued)
    The County Surveyors’ Society 1991
     suggests three ways for monitoring a
     site
    1.   Pay careful attention to a site immediately
         after treatment
         •   In case things go badly wrong
    2.   Assess the effect over a longer time period
         •   About three years to determine the influence of
             treatment on crashes or other performance
             measures
         •   This needs careful statistical analysis to correct
             for external factors
    The need fro monitoring
    (continued)
    3.   Focus on the accident types which the
         treatment was intended to correct
            Assess whether these have in fact declined
    Monitoring and evaluation is meaningful if
        there has been a clear statement of
         objectives of the treatment
        A prediction of its effects
        A logical link between treatment and its
         effects
    Monitoring should apply to all accident
     investigation and prevention work
        The need fro monitoring
        (continued)
   Road safety treatments potentially affect the
    following parameters which need to be
    monitored
       The number and type of crashes
       The severity of crashes
       The distribution of crashes over the road network
       Traffic flows and travel times
       Turning movements and delays at intersections
       Access times and distances within residential areas
       Route taken by motorists, cyclists and pedestrians
       Operation of buses
        The need fro monitoring
        (continued)
   A comprehensive monitoring practice should
    involve all these effects
   Since crashes are relatively rare event, it may
    take a very long time to acquire a statistically
    reliable sample, which makes monitoring difficult
       This can be partially overcome by the use of proxy
        measures such as
         • Traffic conflict measures
         • Indirect measures
            • Insurance company claim record
            • Emergency service records
                • Ambulance, hospital admission
            • Tow truck records
     The need fro monitoring
     (continued)
   Resources devoted to monitoring in most
    agencies are limited
       Resources should be devoted directly to
        development and implementation of treatments
        which have been prioritized and shown to have
        potential for crash reduction rather than
        monitoring exercises
       We should admit that our understanding of safety
        effectiveness of road safety engineering
        treatments is limited and in many cases rests on
        shaky foundation
     The need fro monitoring
     (continued)
   This point comprehensively argued by
    Hauer 1988, who says that
       “the level of safety built into roads is
        largely unpremeditated. Standards and
        practices have evolved without a
        foundation of knowledge. At times the
        safety consequences of engineering
        decisions are not known, at others some
        knowledge exists but not used.”
        Monitoring techniques
   The essence of monitoring is to measure what
    is happening in the real world. There are
    several experimental challenges in doing this
       There may be changes in road environment
         • Change   in   speed limit
         • Change   in   traffic flow
         • Change   in   abutting land uses
         • Change   in   traffic control
       Since crashes are rare and randomly occurring
        events, there will be year by year fluctuations
        which have nothing to do with the treatment
        being analyzed
Monitoring techniques
(continued)
   It is necessary to monitor all significant
    factors which might affect the outcome
   If two variables are systematically related and
    both are measured, it will not be possible to
    reliably isolate their independent effects
   Statistical correlation does not necessary
    imply logical correlation
     • Ensure a linkage between the treatment being
       monitored and the change in performance measure
   Seasonal factors must be taken into account
    Monitoring techniques
    (continued)
    • It would be incorrect to compare the summer (before)
      accident record with the winter (after) accident record
      if one was trying to assess the effect of skid-
      resistance
   Accident reporting levels may change over time,
    and there may be inconsistencies in accident
    data which need to be considered
   There may be a long term trend in crash
    occurrence, therefore changes over time in the
    rate of crashes at a site may merely reflect
    global trends
    • It is usually necessary to use some form of control
      group and compare crashes at the site with those at
      the control site
        Monitoring techniques
        (continued)
   There are four ways that the evaluation of the
    effect of a road safety treatment can be done
       Controlled experimentation
         • All other factors held constant except the factor
           whose effect is being investigated
         • This approach is rarely applicable in road safety
           engineering, because in the real world it is not
           possible to hold everything constant
       Before and after studies
       Comparisons using control sites
       Time trend comparisons
    Before and after studies
   Is the simplest and least satisfactory
    method because of the lack of control of
    extraneous factors and essentially involves
       Determining in advance the relevant objectives
        (e.g. accident types intended to be affected) and
        the corresponding evaluation criteria (e.g.
        accident frequency, accident rate)
       Monitoring the site to obtain numerical values for
        these criteria before and after treatment
       Comparing the before and after results
       Considering whether there are other plausible
        explanations for the change and correct them
        Before and after studies
        (continued)
   Any before and after study, usually relies
    on pre-existing data
       This underlies the need for systematic on-going
        data collection, so the effect of changes can be
        monitored routinely
       Statistical analysis of data should be carefully
        undertaken with regard to accuracy of data
         • It will be helpful to consider more than just changes
           in accident frequency of the particular accident type
         • It may also be useful to check the changes in the 85
           percentile values, variance, skew, etc
     Before and after studies
     (continued)
   For any formal before and after study to be
    statistically valid, a reasonable period of time
    must be considered to obtain a sufficient
    sample
       While one year may be considered a minimum
        analysis period, three years is generally regarded
        as a reasonable period for trends to be
        established and a sufficiently large sample
        obtained
       Nicholson (1987) recommended 5 years for
        statistical confidence
    Comparisons using control sites
    The problem of before and after study is
     that it takes no account for changes across
     the network as a whole
        This can be overcome by using the control
         sites
    There are two variations using control sites
    1.   Using control group which are randomly
         selected
         • A controlled experiment by selecting several
           candidate sites foe a particular treatment in
           advance
Comparisons using control sites
(continued)
 • Then they are randomly split into two groups
    • All sites in the first group and no sites in the second
      group are treated
    • The objective here is to make control and treatment
      groups equal in all factors except for the execution of
      treatment
 • Two groups do not need to be of equal size, but
   they must satisfy sample size requirements
 • This method is powerful as an investigation tool
 • It is of limited validity for most applications in
   roads safety engineering
    • There will barely be the opportunity to conduct a
      controlled experiment of this nature
Comparisons using control sites
(continued)
2.   Using selected comparison groups
        Involves a before and after study
        The result of before and after study will be
         compared with the result of the control site
    The process involves:
        Specifying the objectives in advance
        Identifying a set of control sites
            No remedial work have been or intended to be
             introduced
        Monitoring both the treated and control sites
         before and after treatment to obtain
         numerical values
     Comparisons using control sites
     (continued)
       Comparing the before and after results at both
        the treated and control sites
       Considering if there other plausible explanations
        for the changes and correct them if possible
   Selection of control sites is very important in
    this process and should satisfy the following
    criteria:
       Be similar to treated sites in general
        characteristics
         • Network configuration
         • Geometric standards
         • Land use
        Comparisons using control sites
        (continued)
        • Socio-economic characteristics
        • Enforcement practices, etc
      Be geographically close
      Have similar traffic flows
      Not affected by treatment at the test site
      Not be treated in any way in the period of before
       and after study
      Have crash record which are consistent in both
       collection criteria and coding covering the period of
       study
   A useful device is simply graph the number of crash
    after against the number crash before treatment at
    both test & control sites (Figure 17.1 page 444)
        Time trend comparison
   This method involves the development of a
    model to estimate the trend of accident over
    time which involves the following process:
       Identifying the objectives in advance and the
        corresponding analysis criteria
       Obtaining data on each criteria for an extended
        period of time
       Developing a model based on the before period
       Comparing projections based upon the model for
        after period with the measured criteria for that
        period
       Identifying if there are other plausible
        explanations for the changes and correct them
     Time trend comparison
     (continued)
   This method is useful where substantial
    countermeasure has been produced at a
    given point in time
   Limited application in road safety
    engineering, since it is very difficult to
    control for all variables in real world analysis
   Analytical power of this approach has been
    much extended by the development of log-
    linear models
    Analysis of accident
    statistics
   Three main applications of statistical
    testing in the area of road safety
    engineering are as follow:
       Comparison of crash frequencies
        • A chi-squared test is suitable
        • Or a paired t-test if the distribution of crashes
          can be assumed to be normal
       Comparison of crash rates
        • A paired t-test is appropriate
       Comparison of proportions
        • A z-test is suitable
        (See table 17.1 page 447)
     Analysis of accident
     statistics (continued)
   Poisson distribution is a very simple test for
    calculating probabilities
       Can be used in determining whether a specific
        crash frequency is within the bounds of normal
        year by year fluctuations
   Methodological issues
       There are four important methodological issues
         • Regression to the mean
         • Accident migration
         • Risk compensation
         • Sample size determination
     Regression to mean
   Over a period of time, if there are no changes in
    physical or traffic characteristics at a site, annual
    crashes at that site tend to fluctuate about the
    mean value due to the random nature of crash
    occurrence
   Since the selected sites for treatment are based
    on their ranking in number of crashes compare
    to all other sites, there is a high possibility that
    sites will be chosen when their crash count is
    higher than long term average
   The crash rates at these sites is likely to
    experience a lower rate in the following year
    even without implementing any treatment
        Regression to mean
        (continued)
   This aspect of crash experience need to be
    concerned in after implementation analysis of
    a safety treatment
       Since this phenomenon is present, the impact of
        treatment will be exaggerated
       Regression to mean may exaggerate the effect of
        a treatment from 5-30 percent
       Since our knowledge of safety effects of treatment
        built up from the results of this kind of studies,
        therefore there is a tendency to over-state the
        effectiveness of road and traffic engineering
        treatment
        Regression to mean
        (continued)
   This sometimes called “bias by selection”
    (Hauer 1980)
   Analysts are responsible to separate the real
    benefits from a particular treatment from the
    changes due to regression to mean
    phenomenon
   The problem can be substantially minimized
    by increasing the number of years of data
    used in the site selection process
       This does not solve the problem entirely
       It is not always expedient to wait for several years
        before conducting an evaluation exercise
        Regression to mean
        (continued)
   To correct for regression to mean
    phenomenon, the true underlying accident
    rate should be estimated
       There are two common approaches
        • Model the accident situation in order to estimate the
          true underlying accident rate and then based the
          evaluation on the model not the raw accident data
           • Multi-variate modeling approach developed by Hauer
             (1983, 1992)
        • Adjust the data to correct for biases using
          assumptions about the statistical distribution of
          accidents year by year
     Regression to mean
     (continued)
   Multi-variate modeling approach which extends
    the Empirical Bayes model to allow “unsafety” to
    be estimated when a large reference population
    does not exist
   The model can be described as follows:
     If XB and XA are respectively the accident frequencies
      observed before and after treatment at a site which
      prior to treatment had an underlying mean accident
      frequency m, then the treatment effect, t is given by:
               t = XA / m
    And the regression to the mean effect, r by:
               r = m / XB
     Regression to mean
     (continued)
   If regression to the mean effects are ignored
    it is assumed that
               m = XB
    however, rather than using data for study site
    itself to estimate m, the Empirical Bayes
    approach uses the following expression

             m = a + bxB
    Accident migration
   The assumption here is that accidents may
    increase at sites surrounding the treated site
    due to changes in trip pattern or driver’s
    assessment of risk
       A study in a sample of sites in London show that
        accident at the treated sites fell by 22%, but accident
        in the surrounding street increased by 10%
       The effect of remedial measure for this phenomenon
        is to relocate the accidents not to reduce them
       A statistical explanation for this phenomenon showing
        that there is a spatial correlation between accident
        frequencies at adjacent or nearby sites, so use of
        neighboring sites as control sites leads to bias
        Risk compensation
   Road users adjust their behavior as they
    perceive the road system
       One factor that affect the behavior is perception of
        risk
         • If the the road is perceived as more hazardous then
           drivers may respond accordingly
            • Reducing speed in icy condition
         • Some of the additional road safety provided as a result of
           road safety treatment is used up by drivers behaving in a
           more risky manner
       To make sense of the risk notion in the context of
        road safety engineering, it is important to
        distinguish between objective and subjective risks
     Risk compensation
     (continued)
   Objective risk
       Perceived risk
   Subjective risk
       What affects behavior
   A road safety treatment may
       Reduce the objective risk and increase the
        subjective risk
         • e.g. set of traffic signals both alerts drivers to the hazard
           presented by the intersection and moderating the hazard
           by separating conflicting streams of traffic
       Increase subjective risk alone
         • e.g. warning sign effectiveness depends entirely on
           driver response
    Risk compensation
    (continued)
   Reduce the objective risk alone
     • e.g. skid resistance pavements are not usually discernible
       to the driver
   Reduce both objective risk and subjective risk
     • e.g. improved road geometry, improved sight distance,
       grade separation, etc
     • It is only in this category that risk compensation could be
       a factor, in other categories there is either no change in
       subjective risk or an increase in it
   Any road design change which reduces the
    subjective risk should also reduce the objective
    risk to at least the same extent, otherwise the
    road user will have a tendency to respond
    inappropriately
    Sample size determination
   The smaller the change in accident at any
    site, the larger is the sample necessary to
    determine the statistical significance
       In evaluating a countermeasure, the analyst
        must use either a longer time period or a larger
        number of sites
   The sample size required depends on
       The effect that analyst seek to detect
         • e.g. whether the treatment is expected to decrease
           accidents by 10%, 20%, 50% or so on
       The probability of detecting a real effect
       The level of significance
    Sample size determination
    (continued)
   All feasible combinations of these three
    factors will produce a multitude of outcomes
       (see table 17.2 page 463)

				
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