16 - Simulasi sampel untuk ukuran kumpulan variabel

Utilitas ini dikembangkan sebagai alat tambahan untuk membantu dalam evaluasi validitas dan presisi of different pooling strategies for variable pool sizes. It simulates sampling and prevalence estimation for up to 6 different pooling strategies for and up to 5 different pool sizes for each strategy. Simulations assume perfect test sensitivity and specificity and the specified assumed prevalence in the population. The program runs multiple iterations of sampling and estimation and calculates the mean prevalence and confidence limits for the specified level of confidence across all iterations and estimates the level of bias dalam perkiraan prevalensi.

For each pooling strategy, the program simulates sampling, pooling and testing of individuals from an infinite population with the specified prevalence, using a test of the specified true sensitivity and specificity. Sampling and testing is repeated for the specified number of iterations for each strategy and the prevalence, confidence interval width and variance are estimated for each iteration using the selected method and assumed values of 100% for both sensitivity and specificity. The mean prevalence, bias, confidence interval width and variance are calculated across all iterations for each strategy, where mean bias is the mean prevalence estimate less the true (design) prevalence for the population. Mean square error (mean variance plus square of mean bias) is also calculated, and the magnitude of the mean bias is also calculated as proportions of the mean estimated prevalence, the true (design) prevalence and the mean square error.

The program also allows for the assumed values of 100% for test sensitivity and specificity to be incorrect, allowing assessment of the potential impact of inaccurate estimates on the resulting prevalence estimate.

Input yang diperlukan untuk program ini adalah:

• mengasumsikan prevalensi infeksi yang sebenarnya - antara 0 dan 1;
• sensitivitas dan spesifisitas uji sejati - antara 0 dan 1;
• tingkat kepercayaan yang diinginkan - antara 0 dan 1;
• jumlah iterasi yang akan disimulasikan - bilangan bulat positif; dan
• ukuran dan jumlah kumpulan yang akan diuji untuk setiap strategi yang akan disimulasikan - bilangan bulat positif.

Outputs are summarised across all iterations for each strategy entered and presented in a summary table. The main outputs are:

• berarti prevalensi;
• minimum dan prevalensi maksimum perkiraan;
• mean bias dalam taksiran prevalensi;
• berarti lebar interval kepercayaan;
• berarti kesalahan standar dari taksiran prevalensi;
• berarti kuadrat galat dari perkiraan prevalensi (mean variance plus kuadrat dari bias mean);
• relative bias as a proportion of the mean estimated (apparent) prevalence (AP);
• relative bias as a proportion of the specified design (true) prevalence (TP);
• kuadrat rata-rata bias sebagai proporsi dari kesalahan kuadrat rata-rata;
• the proporsi 'valid' estimasi, di mana interval kepercayaan untuk perkiraan prevalensi berisi prevalensi (desain) yang sebenarnya;
• detailed results for all iterations for each strategy (download as a text file by clicking on the appropriate icon in the summary results table; and
• histogram of the distribution of prevalence estimates (view or download by clicking on the appropriate icon in the summary results table.

It is important to enter pool sizes and associated numbers of pools tested from the top of the table. You must enter at least one valid pool size and number of pools for Strategy 1. All values must be positive integers (>0). Any column in the input table for each strategy that includes an invalid value will be ignored, as will any subsequent values for that stratgey. If the first pool size or number of pools for any strategy is invalid that strategy and any subsequent strategies will be ignored.

This analysis may take several minutes to complete, depending on the number of strategies and the number of iterations required.