Biomedical subjects

Jenö Reiczigel

Publications and source records attributed to Jenö Reiczigel.

3 recordsLinked to original sources

PubMed2005

Properties of crowding indices and statistical tools to analyze parasite crowding data.

Crowding, i.e., the size of the infrapopulation inhabiting an individual host, is a major component of parasites' environment, which often influences both morphological and life-history characters (the so-called density-dependent characters) in different parasite taxa. Although crowding equals intensity in case of a single parasite individual, mean intensity of the host population does not define mean crowding of the parasite population. Crowding indices are notoriously hard to handle statistically because of the inherently large number of nonindependent values in data. In this study, we aim to investigate the apparently paradox features of crowding indices and to make some proposals and also to introduce statistical methods to calculate confidence intervals and 1-sample and 2-sample tests for mean crowding. All methods described in this study are supported by the freely distributed statistical software Quantitative Parasitology.

Animals↗

PubMed2003

Confidence intervals for the binomial parameter: some new considerations.

Several methods have been proposed to construct confidence intervals for the binomial parameter. Some recent papers introduced the "mean coverage" criterion to evaluate the performance of confidence intervals and suggested that exact methods, because of their conservatism, are less useful than asymptotic ones. In these studies, however, exact intervals were always represented by the Clopper-Pearson interval (C-P). Now we focus on Sterne's interval, which is also exact and known to be better than the C-P in the two-sided case. Introducing a computer intensive level-adjustment procedure which allows constructing intervals that are exact in terms of mean coverage, we demonstrate that Sterne's interval performs better than the best asymptotic intervals, even in the mean coverage context. Level adjustment improves the C-P as well, which, with an appropriate level adjustment, becomes equivalent to the mid-P interval. Finally we show that the asymptotic behaviour of the mid-P method is far poorer than is generally expected.

Binomial Distribution↗

PubMedDate not supplied

Evaluation of false transrectal ultrasonographic pregnancy diagnoses in sheep by measuring the plasma level of pregnancy-associated glycoproteins.

The present study was undertaken to investigate to what extent pregnancy diagnoses made by transrectal ultrasonography could be confirmed by measurements of plasma concentration of ovine pregnancy-associated glycoproteins (ovPAG). A total of 424 Awassi x Merino ewes were synchronized for estrus and examined by transrectal ultrasonography. In Experiment 1, the ewes (n = 156) were repeatedly scanned in a standing position on d 29, 36 and 50 of gestation. Similarly, the ewes (n = 268) in Experiment 2 were scanned on d 24, 29 and 34 of gestation, but these ewes were fasted for 12 h prior to the examination and the abdominal wall of each animal was lifted up by the hands of the assistant during the scanning. Blood samples were withdrawn after each transrectal ultrasonographic examination in both experiments. Ovine PAG concentrations were measured in plasma by a heterologous radioimmunoassay and the cut-off value for pregnancy was > or = 1 ng.mL-1. Based on the lambing performance, in Experiment 1, altogether 47 false negative and 38 false positive diagnoses were made by transrectal ultrasonography in 24 and 33 ewes, respectively between d 29 and 50 of gestation. In Experiment 2, altogether 8 false negative and 13 false positive diagnoses both were made in 7 ewes between d 24 and 34 of gestation. In both experiments, all ewes with false negative diagnoses had ovPAG concentrations higher than the threshold level for pregnancy diagnosis and all ewes with false positive diagnoses had ovPAG concentrations lower than the threshold of pregnancy. Furthermore, by the PAG-RIA test all lambed or aborted ewes (n = 63) were correctly diagnosed as pregnant and with three exceptions, all non-lambed ewes (n = 361) were correctly diagnosed as non-pregnant during the examined periods of both experiments.

Animals↗