right. missing information is one thing. but false is another.
perhaps, but i've brought this issue up with them before, and they really like their flawed algorithm. not much chance in getting them to change their method.
i don't know that it's better. their target is the consumer who doesn't want to play researcher and distill through disparate data from various sources, yet that's exactly what's required in order to make useful meaning out of their own data. so they are a bit of a contradiction, in terms of their mission.
i dunno. you know where i stand on this. and this thread is yet another example of another confused consumer because of IFL. how many threads like this have there been in just the past few months? perhaps we could send them a collection of threads exemplifying this, i wonder if that would make then think again about their algorithm. i see plenty of other ways in which they can provide a meaningful score without penalizing specific years or models for missing data. but so far their current method continues to be their favorite.
Aside from treatment of missing data, what is it that is false or flawed in terms of the algorithm? The explain it in great detail. Not everyone has to agree with how they do it or the how they weighted the various inputs, of course, but at least they aren't so secretive as to come up with some mysterious rating with no explanation.
As for confusion, most consumers have no idea how a simple interest loan is calculated, let alone one with the rule of 78s, or the interest and fees on their outstanding credit card balance. Anytime anything more than simple addition is involved, some people will be confused. In that regard, you're absolutely right. Thousands of people had no idea what they could really afford in terms of a mortgage, so wading through something similarly complex is not going to be any easier. On the other hand, the ramifications of a missing piece of data assumed to be average for a composite safety rating seems relatively minor to me, outside of bragging rights if you happen to be a fan or owner of a car penalized for missing results.
I mean really, I don't see much of an option. If a piece of data is missing, that usally means it wasn't carried over by the NHTSA or IIHS. The choice would be to simply leave a model without a full set of data listed as "Incomplete Data". That would probably eliminate a large part of the auto universe, making their rankings of limited utility. On the flipside, perhaps a bigger "asterisk" of some type could be used to indicate that the rating may be higher or lower because of the missing data.