If your data type like that, may be you can analyze via time series analysis in order to PCA. You can read first about economic research method and statistic literature, specialy about regression.

I mean, PCA is pretty much always "appropriate" in that the assumptions pretty much always hold. But does it actually give you any interesting information here? I'm not certain that's the case. Usually you use it when you have thousands of variables and want to pull out vectors which act together, or the vector of variables which cause the most change. For a small system like this? You can easily run each possible regression (vs time, i.e. a time series analysis) and get similar information. 

Thanks Chris. The main question is what method works best for  such data? PCA appears to be a distraction there. Also the Table does not provide all the data.

Analysis of accidents could be a science by itself. PCA could be a starting point for a first analysis of the data.

I think that the dataset is very small because there are external factors that have to be considered, for example weather (rain), visibility, type of road, etc. because at this moment, in this table, you only consider vehicles or human factors.

CD usually have to be the main factor but in this table there is not so clear.

Hi George,

Road crashes are almost always multi-factorial. That is, given a good crash reporting system, you would almost certainly find that the table you present is far too simple. A crash might result from mechanical failure and intoxication and some factor not accounted for such as road condition or weather. The last has already been mentioned. To properly analyze such data, you should also know the baseline prevalence of such things as overloading, poor vehicle condition, etc. For instance in Australia (where I work) almost all vehicles are subject to regular inspection, so it is rare to see one with worn out tires, smoking exhaust and missing parts. Therefore a mechanical failure would be a less common occurrence here. However, in your country it seems that vehicles in poor condition are common, and so mechanical failure is the second most common factor in crashes. It is probably impossible for you to change the crash reporting system, but gathering the information about the prevalence of risk factors in the population and comparing that with the observed crash rate might allow you to state that while many vehicles on the road are in poor condition, only a few are overloaded. This means that the "exposure" of the average driver to poor mechanical condition is much greater than to overloading, and that the latter may be a more important factor as it is less common in the population. If you can obtain information about multiple factors in a crash, perhaps you should look at "multiple cause" analysis. 

Jim Lemon

Transport and Road Safety Research

University of NSW

What is the aim of the research?

Hi Jim

Many thanks for sharing.  I like your proposal to gather information about the prevalence of risk factors in the population and to compare that with the observed crash rate. 

Hi Mohammed

What is the aim of the research? Two reasons: Contribution to the community  and the second motivation is research.

First, my Department (Department of Mathematics) is hoping to put  together short training programs that assist the police department collect, analyze and report its statistical data more accurately (at least less superficially). That, we hope will create more awareness and enable motorists to improve the state of their vehicles.

Second, some of our students want to do their projects in this area of transport and road safety. At the moment, we don't yet have  a clear method for analyzing  the  data .

Dept. of Mathematics

I work as a Policeman in Mijas PD (Spain). I can send you our report model for accidents, but it is in Spanish, in a few days.

Thank you Jose for the offer. Could it be translated to English, using the Web tools?