R help - Mar 2013 - NADA and cenmle

Hi,

I am using the cenmle function from the NADA package and some of my data
are negative values. As a result the cenmle function will not work and
NaN's are produced. I try to change the distribution to Gaussian, but it
still will not run.

Could somebody please help me with this?

Thanks

-- 
Shane

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On Thu, 14 Mar 2013, Shane Carey wrote:
> I am using the cenmle function from the NADA package and some of my data
> are negative values. As a result the cenmle function will not work and
> NaN's are produced. I try to change the distribution to Gaussian, but
it
> still will not run.
>
> Could somebody please help me with this?
   Possibly.

   What do your negative values represent? If they are 'less-thans',
that is,
censored as below the method detection limit or laboratory reporting limit,
then you need to transform them to absolute values and set a flag indicating
their status. For example, your data frame should have a column named
'flag'
or (the lable I use) 'ceneq1' which contains a Boolean value: zero if
the
value is measured and one if it is censored.

   Then write the function call similar to this:

cenmle(dataframe$value, dataframe$ceneq1, dist='lognormal')

   Works as advertised.

Rich

On Thu, 14 Mar 2013, Shane Carey wrote:
> Thanks for your reply. My data frame contains the value and a true/false
> to indicate whether they are censored or not.
>
> So I have something like:
>
> Data          Censored
> -1.2             TRUE
> -5.5             TRUE
> 5                 FALSE
> These negative values are actual values so do these have to be made
> absolute?
Shane,

   If your data represent chemical concentrations of some sort then, yes,
the data must all be positive. You cannot have a chemical concentration less
than zero. If the negative values are actual, then what is the reporting
level? And what do they measure that is really a censored value?

   The concept of censored data, whether right or left censored, is that
there is no way of knowing the actual numeric value. In right-censored
survival analyses (e.g., medical trials) the death of an individual is
recorded. But, when the study ends for whatever reason, there are still
subjects alive and there's no way of knowing how long after the end of the
study they die. Ergo, their age at death is unknown or censored.

   With left censored data such as chemical constituent concentrations in
air, water, or some other medium, there is a concentration below which the
instruments cannot distinguish it from noise. All we know is that the
constituent is present but its concentration is somewhere between zero and
the detection/reporting limit. Therefore, having a number that is below this
detection/reporting limit is meaningless, and it cannot be negative. That's
why it is flagged as being censored. The cenmle() function assumes these
conditions to be true.

   Please keep this thread on the mail list so others can participate and
learn from the conversation.

Rich