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HPMS Publications – Sample Management

Background

The HPMS sample is a stratified random sample of physical roadway sections. The data collected through the HPMS relates to physical characteristics and operating conditions on each of the sampled roadway sections.

Samples are stratified as follows:

State – Rural/small urban/urbanized – Roadway functional system – Traffic volume group

All publicly owned roadway sections meeting the stratum criteria are eligible for selection as a sample on a random basis. The determination of the number of samples needed in each traffic volume group (the sampling rate) is based on the traffic volume (AADT) data item because of its high variability compared to other data items in the HPMS.

Samples are expanded based upon the ratio of total roadway miles in a traffic volume group to the total of sampled miles of roadway in that volume group.

The sample is considered a semi-fixed sample panel. Samples are generally fixed over time; however, they may migrate from one traffic volume group to another, usually because of reclassification of one of the stratum criteria. Since traffic volume is a dynamic variable, sections most often move from one traffic volume group to another as a result of AADT growth. Samples also move when there are changes to their rural/urban characteristics as a result of census population changes, and when the functional class changes as land is developed and the traffic function of a roadway changes. Maintaining the HPMS sample requires the addition (and deletion) of samples over time to account for the shifts of existing sample sections between traffic volume groups.

As a result, active management of the HPMS sample is necessary to assure that the sample continues to represent the full extent of roads in the HPMS, to account for road system changes over time, and to account for the normal growth in traffic. Sample management also allows the State to maintain a cost effective sample plan with neither too many nor too few samples.

Sample Management Practices

There are a number of practices that should guide all sample management activities:

  • Since the HPMS sample is a stratified random sample, sample selections must be made on a random basis from all road sections that meet the stratum criteria. This applies whether new sections are being selected from the full extent for addition to the HPMS sample, or whether existing sample sections are being selected from a stratum for deletion.
  • Additional sampling criteria should not be applied when selecting sample sections. For example, the selection of samples should not be limited to State owned road sections only to the exclusion of roads owned by city or county governments.
  • The HPMS sample should be checked frequently to determine if there are a sufficient number of sections in each traffic volume group. Adjustments to the sample must be made on a random basis.
  • The best time to check sample adequacy is in the period immediately following the annual submittal. This permits any sample adjustments to be made in time to meet the next year's reporting date, and allows ample time to accomplish any additional data collection that might be needed for sample additions.
  • The sample also should be checked to assure that there are at least three samples in each traffic volume group whenever possible. If the traffic volume groups are so small that there are not enough sections to meet the minimum criteria, there should be a review of the traffic data used to assign the sample sections to the traffic volume group to assure that there is a real need for a separate group. If the review shows that a separate small volume group is needed, then all sections should be samples.
  • Attempts should be made to eliminate short sample sections. When a sample section must be split as a result of boundary, functional system, traffic, or other significant roadway characteristic change, the State may wish to eliminate the sample and select a new sample if a split would result in a sample section that does not meet the minimum sample length recommendations (see HPMS Field Manual).
  • Generally, existing samples should not be split for reasons other than those reflected in the HPMS Field Manual.
  • If the expansion factor for a volume group is more than 100, additional sample sections should be selected from the full extent volume group until the expansion factor is reduced to a maximum of 100.

Sample Bias

Samples usually become biased when the State violates the random selection rule or imposes other criteria on the sample selection process. Some activities that result in sample bias include:

  • Selecting only State-owned road sections for HPMS samples;
  • Selecting as an HPMS sample a section adjacent to an existing sample because it is easier to code the same data;
  • Selecting as an HPMS sample a road section in a specific county or highway district because it is convenient for State staff to access and inventory the section; and,
  • Applying other external criteria or conditions to the sample selection process that violate the random selection rule.

Existing HPMS samples may be biased because the State did not apply a random selection process to the original sample. However, as a result of poor sample management practices, even a sample initially selected on a random basis may become biased if samples are added or deleted on other than a random basis over time.

In general, biased samples are best corrected by randomly selecting an entirely new sample. An alternative the State may consider to remedy past bias is to make any further sample adjustments on a random basis; over time, this should lead to a more unbiased sample. Also, the State may consider making specific adjustments to a sample to eliminate bias directly by adding samples in such a way that the effects of the bias are negated. This last process is somewhat complex in that the bias identification, sample analysis, and sample adjustment must be carried out at the traffic volume group level.

For instance, to determine if a rural major collector traffic volume group is biased to State ownership, it would be necessary to look at the ownership of miles in that particular traffic volume group, both full extent and sample. If the sample reflects the inclusion of both State and non-state owned miles, and the representation in the sample and full extent are reasonably similar, it is likely that the sample was chosen in an unbiased manner.

While this may be obvious if there is a substantial representation of both types of ownership in the sample as well as in the full extent, it may be less than clear where the full extent contains very few miles of either ownership type. A full extent comprised of 90% State owned roads could easily yield a sample containing only State owned roads as a result of random selection. On the basis of probability, a full extent comprised of 80% State owned roads could be expected to have between 1 and 3 non-State owned samples out of every 10 as a result of random selection. The best way to determine bias, however, is to know that the State engaged in a biased, non-random, selection process.

If an adjustment to a sample with a clear State owned road bias is necessary, it only should be made at the volume group level. An appropriate adjustment could consist of randomly adding non-State owned road sections to the sample and randomly deleting the same number of State owned road sections until the number of State and non-State owned road sections had similar representation in both the full extent and sample for that particular traffic volume group. This would keep the total number of samples, and hence the sampling rate, the same. This kind of adjustment should not be done routinely and should be considered only where there is clear evidence that a sample has indeed been biased by the use of improper sampling practices.

Sample Management Reviews

A periodic sample management review should be done in cooperation with the State HPMS counterpart. As part of the review of the State's sample management activities, FHWA needs to be able to determine the following:

  • Does the State annually run the sample adequacy software after the HPMS submittal to determine if an adjustment to the sample plan is needed for the next year's data? To be most effective, this should be done immediately after that HPMS data are submitted so as to allow the remainder of the calendar year to be used for making any necessary sample adjustments.
  • Are adjustments to the sample made on a random basis as a result of the adequacy check?
  • Are all public roads on the sampled functional systems included in the pool of full extent sections from which new samples are drawn, regardless of ownership?
  • Is there evidence of sample bias, such as sample clustering on a facility, or within a county, or within a highway district, or is the sample reasonably distributed? This can be determined by looking at a map of HPMS sample locations.
  • Is there sample bias based on State and non-State roads? This comparison needs to be made by volume group within each functional class.
  • Has the State engaged in practices that can result in sample bias in the past? How and where did it occur? Are biased practices still in use? What changes have been made? It is more likely that sample bias may be a problem on the middle functional systems where the State owns fewer of the roads.
  • What remedies are proposed to make up for any existing sample bias?
  • What steps has the State taken to identify and reduce the number of too-short sample sections?
  • Are there volume groups that have expansion factors greater than 100?
  • Has the State adjusted the sample to reflect the latest Census urban boundaries; does the State have a plan to revise the HPMS sample based on these changes?
  • Does the State have a process for adding new roadway miles to the HPMS full extent in a timely manner?
  • Are there unsampled and undersampled volume groups and what is the plan to address them?