14 - Ukuran sampel untuk ukuran kolam tetap dan sensitivitas dan spesifisitas uji tidak pasti

This program calculates the approximate numbers of pools required for a range of pool sizes and specified values for estimated prevalence and desired confidence and precision of the estimate, assuming fixed pool sizes and a test with unknown (uncertain) sensitivity and specificity. Uncertainty associated with the point estimates of test sensitivity and specificity is incorporated through the inclusion of additional variance associated with the sample size used to determine the values used for these parameters. The smaller the sample size, the greater the uncertainty about the true values for sensitivity and/or specificity and hence the greater the uncertainty about the resulting prevalence estimate, resulting in an increased overall sample size to provide the same level of confidence in the estimate. These calculations are based on a re-arrangement of the formulae use to estimate asymptotic confidence limits for pooled prevalence estimates with unknown test sensitivity and specificity (Metode 4).

The required number of pools (m) to estimate the true prevalence with the desired precision is calculated as:

where:

• p = asumsi prevalensi benar;
• k = ukuran kolam;
• Se = sensitivitas uji;
• Sp = spesifisitas pengujian;
• n1 = ukuran sampel untuk memperkirakan sensitivitas tes;
• n2 = ukuran sampel untuk memperkirakan spesifisitas tes;
• e = kesalahan yang dapat diterima (presisi yang diinginkan); dan
• Z = varian normal terstandarisasi yang sesuai dengan tingkat kepercayaan yang diinginkan.

Prevalence estimates calculated from pooled testing may be upwardly biased, particularly as the probability of all pools testing positive increases (high prevalence and/or small numbers of large pools). Therefore, it is advisable to select a lower value for pool size and test a larger number of smaller pools to minimise potential bias in the result, particularly if prevalence is likely to be high. Unlike the situation with a perfect test, it is not possible to determine an optimum pool size to minimise the variance of the estimate if test sensitivity and specificity are uncertain.

Input yang diperlukan untuk analisis ini adalah:

• asumsi prevalensi benar;
• asumsi sensitivitas tes;
• asumsi spesifisitas pengujian;
• ukuran sampel untuk memperkirakan sensitivitas tes;
• ukuran sampel untuk memperkirakan spesifisitas tes;
• tingkat presisi yang diinginkan (atau kesalahan yang dapat diterima); dan
• tingkat kepercayaan yang diinginkan pada hasil.

For example, you might wish to estimate the prevalence where the true value is assumed to be about 0.01 (1%), and you wish to have 95% (0.95) confidence that the true value is within +/- 0.005 (0.5%) of your estimate, with a test that has a sensitivity of 0.9 (90%) and specificity of 0.99 (99%) and where sensitivity and specificity were estimated using sample sizes of 100 and 1000 respectively. The assumed prevalence, desired precision and level of confidence must all be >0 and <1. Test sensitivity and specificity must both be >0 and <=1. Sample sizes for estimating sensitivity and specificity must be positive integers. The larger the sample size the lower the uncertainty and hence the greater the confidence achieved in the estimate.

You can also input a suggested pool size if desired, and the program will calculate the corresponding number of pools to be tested for that pool size (in addition to predetermined pool sizes). Suggested pool size is ignored if it is zero.

Keluaran dari analisis adalah:

• jumlah kumpulan yang diperlukan untuk skenario input dan ukuran kumpulan yang disarankan;
• a table of the numbers of pools (and total number of samples) required for the input-scenario for various pool sizes ranging from 1 to 500; and
• grafik jumlah kolam vs ukuran kolam.