Cost-effective sample size

A model has been developed for determining a cost-effective sample size (n) when estimating cost (8). 

Chip-based and other nanotechnology applications continue to excite much interest in analytical chemistry. Miniaturised devices offer the potential to shrink normal analytical systems with advantage of speed, initial cost, portability, sample size, lower consumables usage and disposability. ED would seem to be a natural choice for such systems since EC effects work fundamentally at a nanoscale. 

A problem long appreciated in economic evaluations, but whose seriousness has perhaps been underestimated (Sturm et al, 1999), is that a sample size sufficient to power a clinical evaluation may be too small for an economic evaluation. This is mainly because the economic criterion variable (cost or cost-effectiveness) shows a tendency to be highly skewed. (One common source of such a skew is that a small proportion of people in a sample make high use of costly in-patient services.) This often means that a trade-off has to be made between a sample large enough for a fully powered economic evaluation, and an affordable research study. Questions also need to be asked about what constitutes a meaningful cost or cost-effectiveness difference, and whether the precision (type I error) of a cost test could be lower than with an effectiveness test (O Brien et al, 1994). 

Clinical trials are costly to conduct, and results are often critical to the commercial viability of a phytochemical product. Seemingly minor decisions, such as which measurement tool to use or a single entry criterion, can produce thousands of dollars in additional costs. Likewise, a great deal of time, effort and money can be saved by having experts review the study protocol to provide feedback regarding ways to improve efficiency, reduce subject burden and insure that the objectives are being met in the most scientifically sound and cost-effective manner possible. In particular, I recommend that an expert statistician is consulted regarding sample size and power and that the assumptions used in these calculations are reviewed carefully with one or more clinicians. It is not uncommon to see two studies with very similar objectives, which vary by two-fold in the number of subjects under study. Often this can be explained by differences in the assumptions employed in the sample size calculations. 

One of the most dependably accurate methods for deriving 95% confidence intervals for cost-effectiveness ratios is the nonparametric bootstrap method. In this method, one resamples from the smdy sample and computes cost-effectiveness ratios in each of the multiple samples. To do so requires one to (1) draw a sample of size n with replacement from the empiric distribution and use it to compute a cost-effectiveness ratio (2) repeat this sampling and calculation of the ratio (by convention, at least 1000 times for confidence intervals) (3) order the repeated estimates of the ratio from lowest (best) to highest (worst) and (4) identify a 95% confidence interval from this rank-ordered distribution. The percentile method is one of the simplest means of identifying a confidence interval, but it may not be as accurate as other methods. When using 1,000... 

Laska EM, Meisner M, Seigel C. Power and sample size in cost-effectiveness analysis. Med Decis Making 1999 19 339-43. 

Table 3.15 summarizes the advantages and disadvantages of various extraction techniques used in the analysis of semivolatile organic analytes in solid samples. They are compared on the basis of matrix effect, equipment cost, solvent use, extraction time, sample size, automation/unattended operation, selectivity, sample throughput, applicability, filtration requirement, and the need for evaporation/concentration. The examples that follow show the differences among these techniques in real-world applications. 

This may be either a continuous process, used when the sample size is relatively large (1 ml or more), or a discrete process, used with samples of less than 20 /il. Continuous-flow systems are simpler to use and more precise, but they are less sensitive. They employ a nebulizer in association with a flame or gas plasma, and either a rotating electrode (Rotrode) or drip-feed to the electrode with the arc or spark. The pneumatic nebulizer has an efficiency of 5-10% and generates an inhomogeneous aerosol. Efiiciency can be improved by proper design of the nebulizer and spray chamber (N4), by use of heated nebulizer gas (R6) or ultrasonic devices (S23). The maximum improvement is a 5- to 10-fold increase in sensitivity. There is also an increase in the complexity and cost of the instrument which usually offsets these benefits. The effect... 

Bohdan Automation, Inc The Balance Automator offers a cost-effective alternative to manual weighing, reduces errors and operator tedium, and processes up to 120 samples per hour. This system can accommoda-tevarious container sizes and balances with the help ofinterchangeable parts. 

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