Abstract
This paper gives an overview of several (mostly recent) statistical contributions to the theory of Limiting and Serial Dilution Assays (LDA's, SDA's). A simple and useful method is presented for the setup of a design for an LDA or an SDA. This method is based on several user-supplied design parameters, consisting in the researcher's advance information and other parameters inherent to the particular problem. The commonly used Maximum Likelihood (ML) and Minimum Chi-square methods for the estimation of the unknown parameter in an LDA or an SDA are described and compared to several bias-reducing estimation methods, e.g. jackknife and bootstrap versions of the ML method. One particular jackknife version is recommended.
Original language | Undefined |
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Pages (from-to) | - |
Number of pages | 0 |
Journal | Statistica Neerlandica |
Volume | 0 |
Issue number | 44 |
DOIs | |
Publication status | Published - 1990 |
Keywords
- jackknife
- minimum chi-square
- IR-70894
- METIS-140482
- Bootstrap
- Maximum Likelihood
- Monte Carlo comparison
- Experimental design