Person: Polleichtner, Christian
Lade...
E-Mail-Adresse
Geburtsdatum
Forschungsvorhaben
Organisationseinheiten
Berufsbeschreibung
Nachname
Polleichtner
Vorname
Christian
Name
2 Ergebnisse
Suchergebnisse
Gerade angezeigt 1 - 2 von 2
Veröffentlichung An alternative approach to overcome shortcomings with multiple testing of binary data in ecotoxicology(2017) Lehmann, René; Bachmann, Jean; Karaoglan, Bilgin; Lacker, Jens; Polleichtner, ChristianBinary data such as survival, hatching and mortality are assumed to be best described by a binomial distribution. This article provides a simple and straight forward approach for derivation of a no/lowest observed effect level (NOEL/LOEL) in a one-to-many control versus treatments setup. Practically, NOEL and LOEL values can be derived by means of different procedures, e.g. using Fisher̷s exact test in coherence with adjusted p values. However, using adjusted p values heavily decreases statistical power. Alternatively, multiple t tests (e.g. Dunnett test procedure) together with arcsin-square-root transformations can be applied in order to account for variance heterogeneity of binomial data. Arcsin-square-root transformation, however, violates normal distribution because transformed data are constrained, while normal distribution provides data in the range (-8,8). Furthermore, results of statistical tests relying on an approximate normal distribution are approximate too. When testing for trends in probabilities of success (probs), the step down CochranŃArmitage trend test (CA) can be applied. The test statistic used is approximately normal. However, if probs approach 0 or 1, normal approximation of the null-distribution is suboptimal. Thus, critical values and p values lack statistical accuracy. We propose applying the closure principle (CP) and FisherŃFreemanŃHalton test (FISH). The resulting CPFISH can solve the problems mentioned above. CP is used to overcome a-inflation while FISH is applied to test for differences in probs between the control and any subset of treatment groups. Its applicability is presented by means of real data sets. Additionally, we performed a simulation study of 81 different setups (differing numbers of control replicates, numbers of treatments etc.), and compared the results of CPFISH to CA allowing us to point out the advantages and disadvantages of the CPFISH. Quelle: linkspringer.comVeröffentlichung The CPCAT as a novel tool to overcome the shortcomings of NOEC/LOEC statistics in ecotoxicology(2018) Lehmann, René; Bachmann, Jean; Karaoglan, Bilgin; Lacker, Jens; Polleichtner, ChristianSpecies reproduction is an important determinant of population dynamics. As such, this is an important parameter in environmental risk assessment. The closure principle computational approach test (CPCAT) was recently proposed as a method to derive a NOEC/LOEC for reproduction count data such as the number of juvenile Daphnia. The Poisson distribution used by CPCAT can be too restrictive as a model of the data-generating process. In practice, the generalized Poisson distribution could be more appropriate, as it allows for inequality of the population mean ÎÌ and the population variance ÏĆ2 . It is of fundamental interest to explore the statistical power of CPCAT and the probability of determining a regulatory relevant effect correctly. Using a simulation, we varied between Poisson distribution ( ÎÌ=ÏĆ2 ) and generalized Poisson distribution allowing for over-dispersion ( ÎÌ<ÏĆ2 ) and under-dispersion ( ÎÌ>ÏĆ2 ). The results indicated that the probability of detecting the LOEC/NOEC correctly was â 0.8 provided the effect was at least 20% above or below the mean level of the control group and mean reproduction of the control was at least 50 individuals while over-dispersion was missing. Specifically, under-dispersion increased, whereas over-dispersion reduced the statistical power of the CPCAT. Using the well-known Hampel identifier, we propose a simple and straight forward method to assess whether the data-generating process of real data could be over- or under-dispersed.