---
title: "Effectiveness of Airbags -- 1998 to 2010 in the US"
author: "John Maindonald, Statistics Research Associates"
date: '`r format(Sys.Date(),"%d %B %Y")`'
documentclass: article
classoption: b5paper
fontsize: 10pt
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    base_format: prettydoc::html_pretty
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pkgdown:
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vignette: >
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  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
bibliography: mr.bib
header-includes:
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---

```{r setup, cache=FALSE, echo=FALSE}
library(knitr)
options(replace.assign=FALSE,width=72)
opts_chunk$set(fig.align='center', fig.width=6.25,
               fig.height=4.25, tidy=FALSE, comment=NA)
knit_hooks$set(par=function(before, options, envir){
if (before && options$fig.show!='none') par(mar=c(4,4,2.6,.1),
              cex.lab=.95,cex.axis=.9,mgp=c(2,.7,0),tcl=-.3)
}, crop=hook_pdfcrop)
oldopt <- options(digits=4)
```

# An analysis based on crashes where there is a harmful event

The US National Highway Traffic Safety Administration (NHTSA) collects,
using a random sampling method, data from all police-reported crashes in
which there is a harmful event (people or property), and from which at
least one vehicle is towed. The data frame \texttt{nassCDS}
(\textit{DAAG}) is derived from NHTSA data for the years 1997 --
2002.\footnote{They hold a subset of the columns
  from a corrected version of the data analyzed in \citet{Meyer_Finney_2005}.
  See also \texttt{help(nassCDS)}. More complete data are available,
  in R image file format, from the web page
  \url{https://maths-people.anu.edu.au/~johnm/datasets/airbags/} (R image
  file).}

Data collection used a complex sampling scheme in which the sampling
fraction differs between observations. Each point has to be multiplied
by the inverse of the relevant sampling fraction, to get a proper
estimate of its contribution to the total number of accidents. The
column \texttt{weight} (\texttt{national} = \textit{national
  inflation factor} in the original SAS dataset) gives the relevant
multiplier.

\Citet{Meyer_Finney_2005} argue that on balance (over the period when
their data were collected), airbags cost lives. After adjustment both
for seatbelt use and for speed of impact, airbags appear on balance to
be dangerous. The apparent effects, most serious in high impact
accidents, are however at the level of statistical error.

Strictly, the conclusion is that, conditional on involvement in an
accident that was sufficiently serious to be included in the database,
and conditioning also on \texttt{seatbelt} (seatbelt use or not) and
\texttt{dvcat} (force of impact) there is a suggestion that airbags are
harmful. Conditional on the airbag failing to prevent an outcome that is
somewhat serious, there is a suggestion that airbags are harmful!
Additionally, there are other factors on which the effects of airbag use
could and likely should be conditioned.

Meyer and Finney's analysis is open to serious challenge. \Citet{Farmer}
argues that these data have too many uncertainties and sources of
potential bias, including issues of what factors should be used for
conditioning, to give reliable results.

# The (Fatality Analysis Recording System (FARS) data

Farmer (2006) presented results from a different analysis that used used
a data series that was designed to record outcomes from all accidents in
which there was at least one fatality. Farmer used front seat passenger
mortality, in cars without passenger airbags, as a standard against
which to compare driver mortality. Limiting attention to cars with no
passenger airbag, the analysis compares the ratio of driver mortality to
passenger mortality between cars with a driver airbag and those without
a driver airbag. An airbag is counted as available (really, potentially
available) if a bag had at some previous time been installed. The
breakdown, based on \`availability,' is designed to check the
effectiveness of installing airbags into cars.

Annual data may be downloaded from
\url{https://www.nhtsa.gov/node/97996/251}. The url
\url{http://www-fars.nhtsa.dot.gov/Main/index.aspx} gives access to a
web-based interface to the data from 2004. Results for 1998 are:

```{r ratio1998}
library(gamclass)
tabAaDeaths <- tabFarsDead(dset=FARS)[['airbagAvail']]["1998", , ]
round(tabAaDeaths, 3)
```

One would expect factors such as seatbelt availability and velocity of
impact to affect passengers and drivers similarly. The ratio of driver
deaths to passenger deaths is 0.823 when airbags are fitted, against
0.940 without airbags. Airbags appear then to have reduced driver deaths
from 0.940 of passenger deaths to 0.823 of passenger deaths, i.e., by a
factor of 0.8755, or a reduction of 12.45%.

Figure \@ref(fig:plotFars) shows the results graphically, for the years
1998 - 2010, based on data are taken from the dataset `gamclass::FARS`.
Airbag availability data, which are the more relevant data, were not
available for 2009 and 2010. Data are for frontal impact.

```{r cap1}
cap1 <- 'With/without ratio of the ratio of driver death rates
  to passenger death rates:
  (a) w/wo driver airbag (not available for 2009 and 2010); (b) w/wo airbag deployment,
  (c) w/wo driver restraint (mainly seatbelt).'
```

```{r plotFars, fig.cap=cap1, out.width='60%', fig.show='hold'}
plotFars(tabDeaths=gamclass::frontDeaths,
          statistics = c("airbagAvail", "airbagDeploy", "restraint"))
```

# Why not compare deployment with non-deployment

Airbags, if properly tuned, will deploy only when the risk of death is
high. Comparison between accidents where bags deploy and accidents where
they do not is at the same time, in part, a comparison between a low
risk situation and a high risk situation -- not a fair comparison.

# Not all airbags are equal!

Airbags that meet current standards are designed to deploy only in
accidents that appear serious enough, as e.g. measured by force of
impact, that deployment is likely to do more good than harm. The 2008
result, where presence of an airbag gives a much lower ratio than
deployment, is what might be expected if airbags deploy only in the most
serious accidents, where the risk of death is anyway high. The 2002 and
2006 results may reflects problems with particular batches of airbags,
such as led to the recall of Takata airbags. For the type of bags that
have been the main focus of attention, long term exposure to heat and
humidity could cause the ammonium nitrate used as propellant in these
bags to explode. See
\url{https://www.nhtsa.gov/equipment/takata-recall-spotlight}.

# Other factors

There may of course be effects from other factors on the driver to
passenger death ratio. These can be checked -- broad checks should be
adequate in revealing anything of consequence.

Data for side and rear impact, and for under or over impact, show
patterns that are much less clear. The relative death rates for side and
rear deaths were both under 1.0 in 2008.

# The above analyses make an important point

In Meyer's analysis, there were many factors that could influence the
risk of death -- so many that the attempt to account for them all led to
an analysis in which statistical noise made it impossible to reach
useful conclusions about the parameter of interest. After adjusting for
the effect of seatbelts, there were a number of other factors whose
effects were similar to or greater than the airbag effect that was the
chief interest of the analysis

A much simpler analysis was however possible, allowing an estimate that
was pretty much unaffected by the factors that affected the death rate
itself. This neatly avoided problems that, in the death count summary
tables, arose from the need to account for many different factors.

Data summarization, or an equivalent use of regression methodology,
cannot deliver a clear conclusion in cases where there are many
different possible choices of the regression equation, and where the
conclusion depends on the equation that is chosen. If an alternative is
available that can avoid or largely avoid the need to account for many
different explanatory variables, this is the preferred strategy.

Changes since 2008 in airbag design and in the mechanisms for triggering
deployment mean that the results presented in Figure \@ref(fig:plotFars)
have limited relevance to judging the effectiveness of airbags in use a
decade or more later. The methodological issues that affect these
analyses remain as important as ever. Papers that assess the impact of
changes in airbag design and deployment include @braver2010have and
@cummings2010accounting. See also `?gamclass::FARS`.

# References
