Sample size changing parameters

The types of data available at the end of a clinical trial will depend upon the trial s sample size, duration, and clinical endpoint. There are two categories of clinical endpoints considered in pharmacoeco-nomic analysis intermediate endpoints and final endpoints. An intermediate endpoint is a clinical parameter, such as systolic blood pressure, which varies as a result of therapy. A final endpoint is an outcome variable, such as change in survival, or quality-adjusted survival, that is common to several economic trials, which allows for comparisons of economic data across clinical studies and is of relevance to policy makers. 

If compounds are detected in lower concentrations than desirable because of detection limits and no leaks have occurred, sample size, gas flow rate, and isolation time can be adjusted to increase the total volatile quantity collected. The method can be optimized efficiently using trial runs in which one parameter is changed at a time. Be aware that volatile ratios will likely be affected by adjustments in these parameters. 

In order to obtain reproducible results and characteristic pyrograms, one must define the optimal experimental parameters, which must then be strictly standardized, as the thermal degradation of a polymer is often sensitive to even minor changes in the pyrolysis conditions. Apart from the cell type, the determining experimental parameters are (1) the pyrolysis temperature and time, (2) the sample size and shape, (3) the nature and velocity of the carrier gas and (4) the chromatographic separation conditions. Let us now consider in greater detail the effect of the above factors on the yield of pyrolysis products and the specificity of pyrolysis. 

Figure 5.9 shows a number of chromatograms obtained using columns with a range of internal diameters, stationary phases, and film thickness. Note the carrier gas velocity, coliunn temperature, sample size and detector used, also changes in elution order, retention times and analysis time reflecting the column parameters. 

This choice for a parameter evaluation criterion is quite fundamental since - in line with the semi-probabihstic safety format - we are interested in the average fraction defectives of the outgoing lots. No arbitrary assiunptions have to be introduced for evaluating an operating characteristic, and no discussion about balancing risks between different parties is necessary. Furthermore, the consequences of changes in sample size are balanced between die two parties involved (Taerwe 1986, Taerwe Caspeele 2006). 

Evaluation of Equation [3.50] shows, for example, that if all other parameters are the same, changing from a column with i.d. 2.1 mm to a 300 jxm capillary will result in a 50-fold increase in the concentration of the analyte as it elutes from the column into the detector, with corresponding increases in peak height (and also peak area depending on whether the detector is concentration or mass flow dependent, see Section 4.4.8). Note, however, that such a comparison is valid only if aU parameters other than i.d. are maintained the same in particnlar this comparison assumes that it is possible to load the same amount of analyte in both cases, a real limitation since the sample size that can be injected without overloading a column is proportional to the amount of stationary phase... 

---