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National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL Session 38 Alcohol Imputation Model Why.

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Presentation on theme: "National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL Session 38 Alcohol Imputation Model Why."— Presentation transcript:

1 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL Session 38 Alcohol Imputation Model Why Impute? Joseph (Joe) M. Tessmer Mathematical Analysis Division

2 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 2 Why?

3 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 3 There is a problem in Alcohol Reporting

4 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 4 Wide range of BAC reporting of drivers and non-occupants by states  Levels of reporting alcohol test results for drivers and non-occupants involved in fatal crashes ranged by states from: Less than 12 Percent to More than 86 Percent

5 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 5 Why Impute ?  Reduce Potential Biases in Estimates  14 % to 88 % of the BAC test results are missing in FARS – dependent on the state  Nationally, approximately 60 % of BAC data are missing for drivers and non-occupants

6 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 6 Why Impute ?  If the individuals selected for BAC level testing is not a random sample, the estimates will be biased  Often only drivers suspected of a high BAC are tested  We would over-estimate BAC levels  44 % of tested individuals had BAC > 0

7 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 7 Current Imputation Procedure  3 Level discriminant analysis  For each missing BAC number calculate the probability that  1) BAC = 0  2) 0 < BAC < 0.1  3) 0.1 <= BAC  Note the probabilities add to 1

8 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 8 Current Imputation Procedure  Provides some useful information  It was a major step forward when introduced in 1986  It is a rigid procedure and can not be used to quantify the effect of the current 0.08 BAC legislation

9 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 9 Current Imputation Procedure  Results can not be used as input to other types of analysis  Can not be used as an independent variable in crash analysis  Can be used as a weight

10 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 10 Why Change to Multiple Imputation ?  State of the art solution  Imputed values are actual BAC levels which can be used in additional analysis.

11 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 11 Why Change to Multiple Imputation ?  Improve fidelity of results  Permits analysis at any level of BAC  Old technique uses the probability that value falls within one of three ranges [More difficult to use.]

12 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 12 Why Change to Multiple Imputation ?  Can calculate the standard error of the estimates.  Achieve greater confidence in results (narrower confidence limits)

13 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 13 Multiple Imputation Advantages  Uses several characteristics of the crash and of the driver or non-occupant to estimate BAC levels.

14 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 14 Example 1  Driver Characteristics  Female Driver  36 years old  Seat belt used  Crash Characteristics  8:20 a.m. Tuesday in October  3 passengers all children in vehicle  2 Vehicles involved  Police reported no drinking and no BAC data  Estimated BAC = 0.0

15 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 15 Example 2  Driver Characteristics  Male Driver  23 years old  Seatbelt not used  Crash Characteristics  2:10 a.m. Saturday in July  No passengers  Single vehicle crash  Police reported drinking but no BAC data Estimated BAC = 0.14

16 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 16 Example 3  Driver Characteristics  Male Driver  23 years old  Seatbelt not used  Crash Characteristics  2:10 a.m. Saturday in July  No passengers  Single vehicle crash  Police reported no drinking and no BAC data  Estimated BAC = 0.00

17 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 17  Multiple Imputation is a lot of work...  Uses several characteristics of the crash and of the driver or non-occupant to estimate 10 BAC levels for each case w/missing BAC.  Does it work?  Are the numbers right?

18 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 18  Yes!!

19 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 19 Verification Test  Select a year of FARS data  Restrict data to known BAC data  Randomly recoded 25 % of known BAC “data missing”

20 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 20 Verification Test  Impute the “missing data”, based on 75% remaining data  Compare estimates vs. the actual data  Repeat test.

21 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 21 Verification Test BAC Estimates for the 25% Removed 19931995 0.01+0.1+0.01+0.1+ Percent Total Drivers Involved Known46.036.943.734.7 MI45.737.743.635.7 Percent Total Drivers Killed (Daytime) Known20.615.921.015.5 MI21.518.021.517.7

22 National Center for Statistics & Analysis People Saving People 28 th Annual Traffic Records Forum, Orlando, FL 22 QUESTIONS?


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