Modern gas chromatographs are expected to deliver the highest performance levels, but actual performance can suffer due to
a number of causes including inappropriate methodology as well as improper instrument setup and poor maintenance. It is always
important to keep accurate and complete records of periodic test or validation mixture analyses and any changes to instrument
configuration, the methods used, and samples run to help diagnose problems when they occur. Sometimes a problem is obvious,
but often something seems to be going wrong while there is no obvious failure. Retention times begin to drift, area counts
start to decrease, or repeat results seem more scattered than before. Deciding if these subtle changes are significant is
not a trivial task. If there is a significant problem, then additional steps can be taken to diagnose and resolve it. If the
problem is insignificant, then considerable time might be saved.
Later on Monday
John V. Hinshaw
The first installment of this column series presented a situation in which an initial chromatogram from Monday morning gave
retention times that seemed to fall outside the range of expected values based upon observations from the most recent runs
obtained on Friday of the previous week. For one peak the average retention time in 10 chromatograms from Friday's data was
14.38 min and the standard deviation of those retention times was 0.011 min. The first run on Monday eluted this peak at 14.41
min; 2.7 standard deviations removed from Friday's average value. At issue was whether this difference between Friday and
Monday was significant and required attention, or if this was an acceptable occurrence that could be ignored safely. If the
change were significant, a chromatographer might decide that he or she should pay close attention to the instrument in question
because its retention times had shifted significantly over the weekend. There are many possible fault conditions that could
result in drifting retention times. Is there a septum leak? Is the pressure controller drifting? How stable is the gas chromatograph's
oven temperature? Our analyst needs to distinguish a developing or full-blown problem that affects data integrity — in this
case our ability to identify peaks on the basis of their retention times — from fluctuations that occur in the course of normal
daily operations.
Table I: Retention times on Friday and the next Monday
A conclusion that there is a retention time shift is a weak one, however, for at least two reasons. First, deciding to pursue
a potential retention time problem on the basis of a single sample — let alone the first sample on Monday morning — would
be a difficult choice to justify. Second, Friday's 10 observations represent a small sampling of a much larger collection
of acceptable experimental outcomes for this peak's retention time, which necessarily covers an observation period longer
than a single day. Due to normal variations the average and standard deviation of one day's worth of observed retention times
could be different than for a more populous set of retention data acquired over the course of a week or a month. Student's
t-test, introduced in the first part of this discussion, helps a small data set better model the expected behavior of the larger
set that it represents by compensating for the tendency of small sample collections to appear more spread out than the overall
population being sampled. In our example, the standard deviation of Friday's 10 samples is assumed to exaggerate somewhat
the distribution of the greater population at large. According to this metric, Monday's first retention time was more than
98% likely not to be a member of Friday's data set.
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