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Biomedical subjects

J Glaz

Publications and source records attributed to J Glaz.

3 recordsLinked to original sources

Power of the scan statistic for detection of clustering.

The scan statistic is the maximum number of events in an interval of fixed length w as the subinterval moves over the entire time frame. Previous research derived the null distribution of the scan statistic under the conditional model which assumed that the total number of events was fixed, and under the unconditional model which let the total number of events be a random variable. This paper derives approximations for the power of the scan test for a pulse alternative. Under this alternative, the relative risk of disease on a subinterval (tau, tau + w), tau unknown, is theta-fold as high as it is for other subintervals of length w. Two sets of approximations are given for each model. The first approximation gives highly accurate results, but requires use of a personal computer. The second procedure can be performed on a hand-held calculator and appears very accurate for the cases examined.

Cluster Analysis↗

Approximations for the tail probabilities and moments of the scan statistic.

The scan statistic is used to test the hypothesis that the observed events occur at random (uniformly distributed) in time or space versus the hypothesis that they cluster within a moving window of size w. To implement the testing procedure based on the scan statistic its tail probabilities have to be effectively evaluated. In this article a survey of results on the approximations of the distribution of the scan statistic and its moments is presented. Numerical results comparing these approximations are also given. Numerous references with applications in epidemiological studies using the scan statistics are mentioned. Related scan statistics that have been used in many other interesting applications are listed in the reference section. The article concludes with the presentation of unsolved problems related to the scan statistic.

Cluster Analysis↗

Expected waiting time for the visual response.

Let the light-quanta be absorbed in the retina according to a Poisson process. The present paper derives bounds for the expected waiting time for an occurrence of a visual response. These bounds can serve as control limits for a proposed coincidence threshold. An upper bound for the probability that a visual response has not occurred in (0,t) is derived and is used to obtain an upper bound for the mean visual threshold.

Humans↗