| Main Title |
Analysis of Coarsely Grouped Data from the Lognormal Distribution. |
| Author |
Hasselblad, Victor ;
Stead, Andrew G. ;
Galke, Warren ;
|
| CORP Author |
Health Effects Research Lab., Research Triangle Park, NC. |
| Year Published |
1980 |
| Report Number |
EPA-600/J-80-299; |
| Stock Number |
PB81-231516 |
| Additional Subjects |
Lead(Metal) ;
Blood chemical analysis ;
Statistical data ;
Reprints ;
Health statistics
|
| Holdings |
| Library |
Call Number |
Additional Info |
Location |
Last
Modified |
Checkout
Status |
| NTIS |
PB81-231516 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
| Collation |
10p |
| Abstract |
A missing information technique is applied to blood lead data that is both grouped and assumed to be lognormally distributed. These maximum likelihood techniques are extended from the simple lognormal case to obtain solutions for a general linear model case. Various models are fitted to the data, and likelihood ratio statistics are computed to test for significance of various parameterizations. The techniques are applied to a data set of over 130,000 blood lead values collected by the city of New York. The data collected from 1970 to 1976, are part of a large-scale screening program and have implications for the current ambient air lead standard. |
