Number of consumers necessary for shelf life estimations based on survival analysis statistics

Survival analysis statistics have been used to estimate shelf life of foods based on consumers’ acceptance or rejection of samples with different storage times. The interval censored nature of the data does not allow regular methods to estimate the number of necessary consumers (N) for these studies. The objective of the present work was to use simulation studies to estimate N considering the error in the estimation, statistical significance and statistical power. Based on previous studies a Weibull model was assumed for the lifetime distribution with a shape parameter r between 0.17 and 0.71. Simulations were calculated supposing shelf-life values in the middle range of an adimensional time scale. Graphs to estimate N under different scenarios are presented. Considering the average r, an alpha value (Type I error) of 5%, a beta value (Type II error) of 20%, the shelf life to be in the middle of the studied time range, and a difference between the true shelf life and the estimated shelf life of 0.5 on a 0–6 time scale, gave an N value of 120 consumers for this particular set of parameters