A Hierarchical Model for the Skew-normal Distribution with Application in Developmental Neurotoxicology

Mehdi Razzaghi

Communications in Statistics - Theory and Methods, 2014, vol. 43, issue 8, 1859-1872

Abstract: The distribution of the mean of a random sample drawn from a skew-normal population was derived by Chen et al. (2004). Here, we consider a hierarchical structure and derive the distribution of the sample mean when the location parameter itself is a random variable with a normal distribution. In neurotoxicological bioassay experiments with laboratory animals, often the response of interest is continuous in nature and the mean of responses is used for inferential purposes (Chen, 2006). However, in developmental neurotoxicity experiments where the neurological effect of a compound on the developing fetus is of interest, because of the intra-litter correlation, the mean of the response distribution may vary from one litter to another. The unconditional distribution of the litter sample mean is derived and its application in the analysis of data from developmental neurotoxicology is described. An example with real experimental data is used to provide further illustration.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2012.675115 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:43:y:2014:i:8:p:1859-1872

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2012.675115

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().