  The aim of this paper is to describe new statistical methods for
determination of the correlations among and distributions of physical
parameters from a multivariate data with general and arbitrary truncations and
selection biases. These methods, developed in collaboration with B. Efron of
Department of Statistics at Stanford, can be used for analysis of combined data
from many surveys with different and varied observational selection criteria.
For clarity we will use the luminosity function of AGNs and its evolution to
demonstrate the methods. We will first describe the general features of data
truncation and present a brief review of past methods of analysis. Then we will
describe the new methods and results from simulations testing their accuracy.
Finally we will present the results from application of the methods to a sample
of quasars.
