PURPOSES We investigated whether patients with organ-confined prostate cancer (PCa) and positive surgical margins (SMs) had a similar biochemical recurrence (BCR) risk compared with patients with pT3a and preoperative prostate-specific antigen (PSA) levels ≤ 10ng/ml. Furthermore, we examined the effects of incorporating SM status, Gleason score (Gls), and preoperative PSA level into the discrim...

Generalized least-squares (GLS ) regression extends ordinary least-squares (OLS) estimation of the normal linear model by providing for possibly unequal error variances and for correlations between different errors. A common application of GLS estimation is to time-series regression, in which it is generally implausible to assume that errors are independent. This appendix to Fox and Weisberg (2...

Recently, path flow estimators (PFE) have been used for the estimation of origin–destination (O–D) matrices. This paper develops a formulation that incorporates a decoupled path flow estimator in a generalized least squares (GLS) framework. The approach seeks to solve a GLS problem that minimizes the sum of errors in traffic counts and O–D matrices based on an equilibrium assignment mapping der...

I study how growth affects liquidity of global stock exchanges and how liquidity determines cross-sectional returns on those stock exchange index portfolios. I measure portfolio liquidity by turnover ratio computed as value of shares traded over the market capitalization. I obtain data from FIBV, an association of global stock exchanges. In a multiple regression model for turnover ratio, I find...

Structural equation models (SEMs) can be estimated using a variety of methods. For complete normally distributed data, two asymptotically efficient estimation methods exist: maximum likelihood (ML) and generalized least squares (GLS). With incomplete normally distributed data, an extension of ML called "full information" ML (FIML), is often the estimation method of choice. An extension of GLS t...

It is well-know that estimation by reduced rank regression is given by the solution to a generalized eigenvalue problem. This paper presents a new proof to establish this result and provides additional insight into the structure of the estimation problem. The proof is a direct algebraic proof that some might find more intuitive than existing proofs. JEL Classification: C3, C32

In this paper we intend to examine the application of Kullback-Leibler, Hellinger and LINEX loss function in Dynamic Linear Model using the real price of oil for 106 years of data from 1913 to 2018 concerning the asymmetric problem in filtering and forecasting. We use DLM form of the basic Hoteling Model under Quadratic loss function, Kullback-Leibler, Hellinger and LINEX trying to address the ...

JEL Classification Code(s): J 31, J 71) "Perceptions of Discrimination, Effort to Obtain Psychological Balance, and Relative Wages: Can We Infer a Happiness Gradient?" There is a substantial literature that finds a linkage between happiness and relative economic well being as measured by earnings or wages. There is also a well documented racial gap in wages. One explanation for this is disparat...

This paper discusses estimation of causal effects of non-randomly assigned binary treatments on binary outcomes. The approach is full information maximum likelihood estimation of endogenously switching nonlinear regressions with a multivariate Student’s-t error structure. An application measures the effect of problem drinking on probability of employment. JEL Classification: I1, C3 I thank the ...