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SS Part B BTS approved (6/17)
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| File Title | SS Part B BTS approved (6/17) |
| Author | Culbreath, Walter (NHTSA) |
| Last Modified By | Daniels, Lorenzo (NHTSA) |
| File Modified | 2026-02-17 |
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Department of Transportation
National Highway Traffic Safety Administration
Information Collection Request Supporting Statements: Part B
Crash Report Sampling System
OMB Control No. 2127-0714
Abstract:1
The National Highway Traffic Safety Administration (NHTSA) is seeking approval from OMB of this information collection request (ICR) for extension with modification of its currently approved information collection for Crash Report Sampling System (CRSS). NHTSA is authorized by 49 U.S.C. § 30182 and 23 U.S.C. § 403 to collect data on motor vehicle traffic crashes to aid in the identification of issues and the development, implementation, and evaluation of motor vehicle and highway safety countermeasures. The information collected serves to identify and develop safety countermeasures that will reduce the severity of injury and property damage caused by motor vehicle crashes.
The Crash Report Sampling System (CRSS) collects data from police-reported crashes involving all types of motor vehicles, pedestrians, and cyclists; this includes property damage only crashes as well as those resulting in injuries and fatalities. CRSS obtains its data from a nationally representative probability sample selected from the estimated six million police-reported crashes that occur annually in the United States. By focusing attention on police-reported crashes, CRSS concentrates on the crashes of greatest concern to the highway safety community and the general public.
CRSS depends on the voluntary participation and cooperation of State and law enforcement agencies. This allows the National Highway Traffic Safety Administration (NHTSA) and its contractors to access the police crash reports (PCRs) to review, list, and categorize the crashes. CRSS data is solely based on PCRs. The PCRs provide essential data: detailed information regarding the location of the crash, the vehicles, and the people involved. The PCRs are official local and State government forms that include the location of the crash and the pre-crash environment, explain the number and types of vehicles involved as well as describing the persons, injuries and other variables to express how the person was involved in the crash. CRSS respondents are local law enforcement agencies and State agencies that provide access to repository/website or database of motor vehicle crashes.
For the PCR data acquisition process, NHTSA’s technicians regularly obtain PCRs from the sampled police agencies and select a sample of the in-scope PCRs. Once a PCR has been selected for data collection, NHTSA’s data coders review and retrieve the general crash information from the sampled PCR. PCR is the sole source for the CRSS data collection.
These information collections support NHTSA’s mission to save lives and prevent injuries due to traffic crashes. The data collected from the CRSS provide annual, nationally representative estimates of the number, types, and characteristics of police-reported motor vehicle crashes. These data are used by NHTSA to support its highway safety research, policy making, and regulation program development.
The previous request for this information collection (OMB No. 2127-0714) indicated 42,680 burden hours, this request decreases the burden to 18,167. The request for the collection of information is adjusted due to a) reducing the burden hour estimates for CRSS information collection to be more accurate and reflect current efficiencies, b) removing the Non-Sampled Police Jurisdiction (PJ) Crash Count Special Study. The removal of the Non-Sampled PJ Crash Count Special Study is the biggest change to the previous clearance. There were two special studies included in the previous clearance, Non-Sampled PJ Count Special Study and PJ Frame Evaluation Special Study. NHTSA determined the PJ Frame Evaluation Special Study is the most critical to assessing the quality of the PJ frame of the CRSS PSUs to address PJ changes and update the PJ measure of size with the latest crash counts for the CRSS PJ sample selection. Without the PJ Frame Evaluation Special Study, NHTSA may fail to accurately assess the national crash picture by missing pertinent crash data. Thus, if the results of the PJ Frame Evaluation Special Study reflects the current PJ landscape, the Non-Sampled PJ Crash Count Special Study is not necessary.
The combined impact is a decrease of 24,513 burden hours to NHTSA’s overall total.
B. COLLECTIONS OF INFORMATION EMPLOYING STATISTICAL METHODS
1. Describe the potential respondent universe and any sampling or other respondent selection methods to be used.
CRSS is a major record-based crash data collection system.2 CRSS is a multi-stage complex survey of police crash reports. CRSS sample is comprised of PSU, PJ, and PCR samples.
In the following, we describe in detail the CRSS population and how the CRSS PSU, PJ, and PCR samples are selected.
The purpose of the CRSS is to provide annual, nationally representative estimates of police-reported motor vehicle crashes as well as characteristics of these motor vehicle crashes. PCR is the sole source of data for the CRSS. CRSS population is the set of police-reported motor vehicle crashes on a traffic-way (strata 2 – 10 of Table 2).
Table 1. CRSS PCR Strata, Target Sample Allocation, and Population Sizes
CRSS
PCR Stratum
Description
Target Percent of Sample Allocation
Estimated
Population
(CRSS2023) ****
Population Percent
1
An in-scope Not-in-Traffic Surveillance (NTS) crash (take all)*
2
Crashes not in Stratum 1 in which:
Involves a killed or injured (includes injury severity unknown) non-motorist
9%
131,072
2.1%
3
Crashes not in Stratum 1 or 2 in which:
Involves a killed or injured (includes injury severity unknown) motorcycle or moped rider
6%
81,967
1.3%
4
Crashes not in Stratum 1-3 in which:
At least one occupant of a late model year passenger vehicle** is killed or incapacitated
4%
20,194
0.3%
5
Crashes not in Stratum 1-4 in which:
At least one occupant of an older passenger vehicle*** is killed or incapacitated
7%
88,363
1.4%
6
Crashes not in Stratum 1-5 in which:
at least one occupant of a late model year passenger vehicle** is injured (including injury severity unknown)
14%
350,873
5.7%
7
Crashes not in Stratum 1-6 in which:
involved at least one medium or heavy truck or bus (includes school bus, transit bus, and motor coach) with GVWR 10,000 lbs. or more
6%
532,028
8.7%
8
Crashes not in Stratum 1-7 in which:
at least one occupant of an older passenger vehicle*** is injured (including injury severity unknown)
12%
862,634
14.1%
9.
Crashes not in Stratum 1-8 in which:
involved at least one late model year passenger vehicle**,
AND
No person in the crash is killed or injured
22%
1,529,202
24.9%
10
Crashes not in Stratum 1-9:
This includes mostly PDO crashes involving a non-motorist, motorcycle, moped, and passenger vehicles that are not late model year** and any crashes not classified in strata 1-9.
20%
2,542,026
41.4%
*: NTS cases are not in the scope of CRSS. They are set aside for NTS analysis.
**: Late model year passenger vehicle: passenger vehicle that are 4 years old or newer.
***: Older passenger vehicle: passenger vehicle that are 5 years old or older.
****: 2023 CRSS estimates are the most recent estimates.
The estimated CRSS population size (strata 2–10 of Table 2) was about 6.1 million in 2023. CRSS selects a sample from the population through a stratified multi-stage cluster scheme as follows:
First Stage (PSU Sampling)
The country is divided into geographic units called Primary Sampling Units (PSUs). A PSU is a county or group of counties and serves as a cluster. PSUs were formed as groups of adjacent counties subject to a minimum measure of size (MOS) condition to ensure enough cases will be sampled from each PSU and weights are approximately equal within each PCR stratum defined in Table 2. The CRSS PSU MOS was defined as:
where
= the PCR stratum defined in Table 2.
= the desired total sample size of crashes
= the desired sample size of crashes in the PCR stratum
= the estimated population count of crashes in the PCR stratum
= the estimated population count of crashes in the PCR stratum and PSU .
In the formula, is the desired PCR strata sample allocation (the “Target Percent of Sample Allocation” column in Table 2), and is the relative estimated population counts of PSU for PCR stratum . In this way, a PSU with a larger high interest (as defined by the oversampled PCR strata defined in Table 2) combination of estimated population counts of all PCR strata has a larger MOS.
PSU formation respects US Census region and urbanicity boundaries. While 23 remote outlying counties in Alaska and three counties of small islands in Hawaii were excluded, the rest of the country is included in the PSU frame. There are 707 CRSS PSUs in the PSU frame.
The PSU frame was then stratified into eight primary PSU strata by two variables – region (Northeast, West, South, and Midwest) and urbanicity (urban and rural). Within each primary stratum, PSUs were further stratified by secondary stratification variables such as vehicle miles traveled, total crashes, truck miles traveled, and road miles by road type. PSUs with similar characteristics were grouped into secondary strata with approximately equal MOS sizes. Secondary strata groupings were also based on minimizing the between-PSU variance within a stratum. As the result, 50 PSU strata were formed as indicated in Table 3.
Table 2. CRSS PSU Strata, PSU Population Counts, and Sample Size
PRIMARY STRATA
STRATID*
VMT_RATE_IMP**
TOT_CRASH
_RATE**
TRK_MI_RATE**
ROAD_TYPE
_RATE**
Number of PSUs
PSU Sample Size
Upper
Lower
Upper
Lower
Upper
Lower
Upper
Lower
1
101
1801
0
359
0
5
2
1
102
4064
1801
359
0
5
2
1
103
7159
4064
359
0
8
2
1
104
5791
0
0.028
0
153756
0
2175
359
6
2
1
105
8040
5791
0.028
0
153756
0
2175
359
7
2
1
106
0.028
0
249918
153756
2175
359
7
2
1
107
0.028
0
591241
249918
2175
359
7
2
1
108
0.039
0.028
2175
359
11
2
2
201
236701
0
22
2
2
202
1027526
236701
22
2
3
301
4135
0
45709
0
3
2
3
302
7465
4135
45709
0
8
2
3
303
9898
7465
45709
0
10
2
3
304
102554
45709
11
2
3
305
4444
0
339758
102554
13
2
3
306
6003
4444
339758
102554
11
2
3
307
11618
6003
339758
102554
10
2
4
401
66171
0
4345
0
28
2
4
402
6045
0
565025
66171
4345
0
27
2
4
403
11623
6045
565025
66171
4345
0
25
2
4
404
17641
4345
30
2
5
501
3620
0
0.048
0
125590
0
5
2
5
502
4530
3620
0.048
0
125590
0
8
2
5
03
4951
4530
0.048
0
125590
0
6
2
5
504
5016
4951
0.048
0
125590
0
3
2
5
505
5277
5016
0.048
0
125590
0
5
2
5
506
5746
5277
0.048
0
125590
0
6
2
5
507
6399
5746
0.048
0
125590
0
5
2
5
508
12826
6399
0.048
0
125590
0
8
2
5
509
5641
0
0.048
0
210430
125590
6
2
5
510
8348
5641
0.048
0
210430
125590
7
2
5
511
13892
8348
0.048
0
210430
125590
10
2
5
512
0.048
0
358684
210430
8
2
5
513
0.048
0
877546
358684
13
2
5
514
0.085
0.048
17
2
6
601
49854
0
35
2
6
602
6353
0
162415
49854
34
2
6
603
14415
6353
162415
49854
35
2
6
604
250190
162415
33
2
6
605
5693
0
1156242
250190
35
2
6
606
16271
5693
1156242
250190
35
2
7
700
1
1
7
701
6477
0
0.027
0
104522
0
7
2
7
702
6921
6477
0.027
0
104522
0
4
2
7
703
7861
6921
0.027
0
104522
0
5
2
7
704
5137
0
0.027
0
249358
104522
3
2
7
705
8070
5137
0.027
0
249358
104522
10
2
7
706
0.048
0.027
92716
0
9
2
7
707
0.048
0.027
186409
92716
7
2
8
801
3938
0
30
2
8
802
18292
3938
41
2
*: STRATID: Secondary PSU ID.
**: VMT_RATE_IMP = imputed vehicle miles traveled / (PSU MOS×1,000,000).
TOT_CRASH_RATE = (imputed 2008 injury crashes + imputed 2008 PDO crashes + 2007-2011 average fatal
crashes) / (PSU MOS×1,000,000).
TRK_MI_RATE = Total truck miles / (PSU MOS×1,000,000).
ROAD_TYPE_RATE = (primary road miles + secondary road miles) / (PSU MOS×1,000,000).
A major challenge of the CRSS sample design is the uncertainty of the future operational budget. Due to unknown future funding levels and the need for a stable PSU sample, NHTSA implemented a scalable PSU sample, which allows for the PSU sample size to be decreased or increased with minimum impact to the existing PSU sample and for the selection probabilities to be tracked. To this end, a multi-phase sampling method was used to select the CRSS PSU sample by selecting a sequence of nested PSU samples. In this method, a PSU sample larger than what is actually needed is selected during the first phase of the PSU sample. From the first phase of the PSU sample, a smaller subset of the PSU sample is selected as the second phase of the PSU sample. From the second phase of the PSU sample, another smaller third phase of the PSU sample is selected. This process is continued until the PSU sample size reaches unacceptable levels. In this way, a sequence of nested PSU samples is obtained. Each of these PSU samples is a probability sample and can be used for data collection (see Figure 2). According to the prevailing budget level, a sample with the appropriate sample size is picked from the nested sequence. This allows us to easily track the selection probabilities and minimizes changes to the existing PSU sample.
Figure 1. Nested PSU Samples for CRSS
For the CRSS, five PSU samples were selected under the five scenarios. Table 4 summarizes the number of PSU strata and sampled PSUs for the CRSS PSU sample scenarios.
Table 3. CRSS PSU Sample Scenarios: Number of Strata and Sample Size
Scenario
Number of PSU Strata
Number of Sampled Non-certainty PSUs
Number of Sampled Certainty PSUs
Total Number of Sampled PSUs
1
50
97
4
101
2
37
74
1
75
3
25
50
1
51
4
12
24
0
24
5
8
16
0
16
For scenario 1, with a sample size of 100 and without stratification, one PSU was identified as a certainty PSU by the condition:
Here N is the total number of PSUs in the PSU frame and i is an index for a PSU. The PSU selected with certainty3 was set aside. Then two PSUs were selected using proportional to size (PPS) sampling from each of the 50 scenario-1 strata. With the sample size of two for each PSU stratum, three PSUs were identified as certainty PSUs by the condition:
Here is the total number of PSUs in stratum . The certainty PSUs selected with certainty were set aside. The corresponding stratum PSU sample size was reduced by one. Then a PPS sample of non-certainty PSUs was selected using the reduced PSU stratum sample size.
Scenario-1 sample has 101 PSUs. For a non-certainty PSU, the selection probability is:
Here be the non-certainty PSU sample size for PSU stratum .
For scenario-2, with a sample size of 74 and without stratification, one PSU was identified as a certainty PSU and was set aside. Then 13 of the scenario-1 strata were collapsed with other strata to form the 37 scenario-2 PSU strata. The collapsing of strata follows the following rules:
• Only the secondary strata in the same primary stratum can be collapsed;
• Only the contiguous secondary strata can be collapsed;
• The resulting strata has a similar stratum total MOS within each primary stratum.
In each of the scenario-2 stratum, the sampled scenario-1 PSUs were treated as the sampling frame. Each PSU was assigned a new MOS equal to its scenario-1 stratum total MOS. Then two PSUs were selected from each scenario-2 stratum using PPS sampling based on the new MOS. In this way, the resulting selection probability of the scenario-2 PSU is still PPS selection probability. Other scenario samples were selected in a similar way.
The current CRSS PSU sample size is 61 (between scenarios 2 and 3) with 60 responding PSUs and one non-responding PSU.
Second Stage (PJ Sampling)
The secondary sampling units (SSU) of CRSS are police jurisdictions (PJs) that produce PCRs for the crashes occurred within the sampled PSUs. A composite MOS is assigned to each PJ in the selected PSUs. Similar to the PSU MOS definition, it is sensible to assign larger selection probabilities to PJs with more high interest crashes as defined by the oversampled strata in Table 2. For each PJ in the selected PSUs, crash counts from the 9 PCR strata in Table 2 (Stratum 2-10) were estimated from the information collected from the PJs in the selected PSUs. For PJ in the PJ frame within the sampled PSU , the composite SSU MOS is defined as the following:
where
= the PCR stratum defined in Table 2.
= the desired total sample size of crashes
= the desired sample size of crashes in the PCR stratum
= the estimated population count of crashes in PCR stratum
= the estimated population count of crashes in PCR stratum , PJ and PSU
PJs are then stratified into two PJ strata by their MOS (large MOS stratum [largest 50%] and small MOS stratum [the rest]) in addition to certainty PJ stratum where all PJs are selected with certainty. A PJ sample is selected using Pareto sampling. The Pareto sampling method produces an approximate PPS sample, handles the frame changes and minimizes the changes to the existing sample at the same time. Pareto sampling method was applied to the PJ sample selection for each of the non-certainty PJ strata (large MOS and small MOS stratum) within the sampled PSU, as the following:
Step 1: Generate a permanent uniform random number for each PJ in the PJ stratum h of PSU i.
Step 2: Identify certainty PJs by the condition:
Here is the PJ sample size and is the PJ frame size for PJ stratum h within PSU i. is the PJ MOS.
Step 3: The identified certainty PJs are set aside. This process is repeated for the remaining PJs based on the reduced PJ sample size until there are no more certainty PJs. Let the total number of certainty PJs be . For the remaining non-certainty PJs in the frame, calculate the PPS inclusion probability with the non-certainty PJ sample size (
Step 4: Calculate the transformed random numbers and sort the transformed random numbers from the smallest to the largest as following:
Step 5: The certainty PJs plus the first non-certainty PJs from the above list are the PJ sample for PJ stratum h within PSU .
Pareto sampling is approximately PPS, and the PJ selection probability is:
The 2023 CRSS PJ sample size is 289.
Third Stage (PCR Sampling)
The tertiary sampling units (TSU) of CRSS are PCRs. The CRSS PCR sample is selected by stratified systematic sampling. For each selected SSU (PJ), PCRs are periodically obtained by either a technician’s visit to the PJ or electronic transmission. All the PCRs are listed in the order they become available and are stratified by the PCR strata identified in Table 2. Through this listing process, the PCR sampling frame in each selected PJ is prepared for PCR sample selection.
For a large PJ with too many PCRs to be listed, PCRs are sub-listed by systematic sampling. For example, only PCRs with a PCR number ending in 0 through 4 may be listed if the sub-listing factor is 2 (i.e., 5 PCRs among 10 PCRs are listed). Or only PCRs with a PCR number ending in 0 or 1 are listed if the sub-listing factor is 5 (i.e., 2 PCRs among 10 PCRs are listed). If PCRs among 10 PCRs are sub-listed in PJ in PSU , the sub-listing probability for all sub-listed PCRs are:
After PCRs are listed, a PCR sample is selected by systematic sampling from the listed (or sub-listed) PCRs by PCR stratum within each selected PJ. The selection probability of PCR from PCR stratum is:
Here is the PSU selection probability, is the PJ selection probability, and is the sub-listing probability. , which is the sampling rate of the PCR stratum , is calculates with the target PCR sample size and the estimated total number of PCRs in the population for the PCRs stratum as:
The overall selection probability is:
The design weight is the inverse of .
Sample Allocation
For a three-stage sample design as this program, the PSU, SSU and TSU sample sizes can be estimated using optimization by minimizing the variance subject to cost assuming a three-stage simple random sampling without replacement.
The optimization model consists of the objective function, cost constraint, and variance constrains as the following:
where
: Subscript of the identified key variable, .
: Proportion estimate of the key variable.
: Optimal sample sizes of PSUs, SSUs per PSU, and TSUs per SSU to be determined.
: Population size of PSUs
: Average population size of SSUs.
: Average population size of TSUs.
: Variance of the identified key estimate .
: Variance component at PSU-, SSU-, and TSU-level.
: Total, fixed, PSU-, SSU-, and TSU-level cost coefficients.
: Variance of the identified key estimate in General Estimates System (GES)4.
Figure 3 displays the optimization results. As the rescaled budget increases, the PJ sample size m and the PCR sample size k tend to be stable while the PSU sample size n increases and the average variance decreases. Since there are 9 PCR domains to be estimated (strata 2-10 in Table 1), the final PCR sample size is 9×k.
Figure 2: Average Variance, PSU, PJ and PCR Sample Size as Functions of Budget
Note: All costs are rescaled, so the lowest cost starts from $1.
Each year, CRSS’s target sample is 50,000 crashes. Below is a table summarizing the CRSS sample. The 2016 CRSS data collection year had only 53 PSUs instead of the full 60 PSUs due to constraints with receiving police crash reports, thus the sample was less than the anticipated 50,000 crashes.
Table 4: Unweighted Summary Statistics
Year
Crashes
Vehicles
People
Drivers
Occupants
Pedestrians
Pedalcyclists
(In-Transport)
2016
46,511
82,149
117,759
82,000
113,405
2,257
1,576
2017
54,969
97,625
138,913
97,388
133,408
2,881
1,946
2018
48,443
86,105
120,230
85,916
115,774
2,444
1,436
2019
54,409
96,717
135,410
96,488
129,980
2,949
1,802
2020
54,745
94,718
131,962
94,500
126,460
2,882
1,923
2021
54,200
95,785
133,734
95,551
128,315
2,886
1,820
2022
53,955
94,756
132,175
94,510
126,442
2,967
1,870
2023
50,103
87,461
122,388
87,262
116,597
2,907
2,050
More information on CRSS Sample Design and Weighting can be found at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812706
2. Describe collection of information procedures.
CRSS data collection efforts are dependent on the method in which the crash reports are accessed. The crash reports are accessed through NHTSA’s Electronic Data Transfer (EDT) program, data feeds, secure email, State websites, or manually by contract staff that physically visit the police jurisdiction.
The EDT program consists of a routine automated transfer of crash data from the State crash database to NHTSA. EDT reduces the level of effort required to share crash data because data is automatically shared nightly from the State to NHTSA. States may also provide crash reports to NHTSA through secure web service portals on a routine basis. The State designates the frequency with which they share data with NHTSA under this protocol. Crash report accessed via EDT and secure web portal are uploaded into the Police Accident Report Sampling Engine (PARSE). The PARSE application is a centralized, web-based repository in which CRSS applicable crash reports are listed, categorized, and selected for further coding. In 2023, over one third (21 out of 60) of CRSS PSUs are EDT PSUs.
Alternatively, States may provide access to their crash data collection websites. States provide log-in credentials to view crash reports for the sample PJs. The sampler would then list, categorize, and sample the crash reports for sample agencies within the PARSE application.
When States are not able to provide electronic access to crash reports, NHTSA seeks manual access to crash reports from individual police jurisdictions identified in the CRSS sample. Generally, this includes visiting the office to access paper or electronic files, uploading crash reports on an encrypted thumb drive, linking crash reports to a secure email or copying crash reports and sending the crash reports via mail courier service. These manual processes are completed on a schedule established by the police agency. Once the schedule is agreed upon, then the CRSS sampler can view, list, categorize, and sample the crash reports within the PARSE application. In 2023 CRSS, for example, NHTSA obtained cooperation from 254 PJs in 39 non-EDT PSUs.
3. Describe methods to maximize response rates and to deal with issues of non-response.
CRSS has a three-stage sample design. The first stage sampling units or PSUs are counties or groups of counties. A PSU becomes a non-responding PSU only if all selected police jurisdictions (PJs) within the PSU are non-responding PJs. Since the PJ sample is selected using the Pareto sampling method, all PJs in the PJ frame can be selected as replacement sample for non-responding PJs. Therefore, a PSU becomes a non-responding PSU only if all PJs in the frame are non-responding PJs. In 2017 CRSS, one PSU was non-responding. Since the CRSS PSU sample is scalable, we increased the sample size from 60 to 61 and selected a replacement PSU without changing the original PSU sample. The weight of the non-responding PSU was adjusted.
The second stage sampling units of CRSS are PJs. A sampled PJ becomes non-responding PJ if it refuses to cooperate. To improve PJ cooperation rate, NHTSA visits each selected PJ and meets with local law enforcement officers to gain cooperation. In 2023 CRSS, 14 PJs among the 268 sampled PJs in non-EDT PSUs were non-responding. The weights of non-responding PJs were adjusted.
The third stage sampling units of CRSS are PCRs. First all police crash reports (PCRs) in the selected PJs are listed. Then a systematic sample of PCRs is selected and coded. A PCR is identified as non-responding if it has un-readable pages or missing pages. In 2023 CRSS for example, only 21 PCRs among the 50,241 sampled PCRs were non-responding. The weights of the non-responding PCRs were adjusted.
The CRSS quality control system is designed to produce the most accurate, reliable, and complete database possible within the limits of available resources. Each selected case is reviewed by quality control personnel for accuracy before proceeding to coding. Additionally, PARSE automatically selects five percent from each sample of non-selected cases to review. The findings from the listed cases review helps identify any quality control issues and additional training needs for the CRSS Sampler.
4. Describe any tests of procedures or methods to be undertaken.
There is no tests procedure to be undertaken at this time.
5. Provide the name and telephone number of individuals consulted on statistical aspects of the design and the name of the agency unit, contractor(s), grantee(s), or other person(s) who will actually collect and/or analyze the information for the agency.
Ms. Chou-Lin Chen, National Center for Statistics and Analysis, NHTSA, is responsible for CISS survey design and special studies.
NHTSA contracted with Westat (contract DTNH22-12-F-00389) on the CRSS survey design effort. NHTSA has contracted with Westat (contract GS00Q14OADU223/ task order 693JJ924F000013) to provide statistical support on the CRSS.
NHTSA has contracted with Laansu Inc. (contract 693JJ921C000009 and 693JJ922C000011) for the data collection, coding and quality control for the CRSS data collection effort.