SISSI (Confalonieri et al., 2007) implements the visual jackknife method for optimal sample size determination (Confalonieri, 2004; Confalonieri et al., 2006; 2009). The method provides a visual evaluation system based on the intensive use of sample data by systematically taking sub-samples of the original data set, and calculating mean and standard deviation for each of subsamples. This approach overcomes the typical limitations of conventional methods, requiring data-matching statistical assumptions.

Visual, easy-to-interpret provisions are supplied to display the variation of means and standard deviations as size of generated samples increases. An automatic option for identification of optimal sample size is given, targeted at the size for which the rate of change of means becomes negligible. Alternatively, a manual option can be applied.

A simplified version of SISSI is available for mobile devices (PocketVJ).

Product Manager: Roberto Confalonieri
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INRA - Institut National de la Recherche Agronomique (France)

2009 - Field Crops Research, 113, 125-130
Analysis of sample size for variables related to plant, soil, and soil microbial respiration in a paddy rice field.
Confalonieri, R., Perego, A., Chiodini, M.E., Scaglia, B., Rosenmund, A.S., Acutis, M.

2007 - Environmental Modelling & Software, 22, 1796-1800
Resampling-based software for estimating optimal sample size.
Confalonieri, R., Acutis, M., Bellocchi, G., Genovese, G.

2006 - Field Crops Research, 97, 135-141
Analysis of rice sample size variability due to development stage, nitrogen fertilization, sowing technique and variety using the visual jackknife.
Confalonieri, R., Stroppiana, D., Boschetti, M., Gusberti, D., Bocchi, S., Acutis, M.

European Commission Joint Research Centre

INRA - Institut national de la recherche agronomique
Department of Primary Industries (DPI)

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