Normalized Equation and Decomposition Analysis: Computation and Inference This paper joins discussions on normalized regression and decomposition equations in devising a simple and general algorithm for obtaining the normalized regression and applying it to the Oaxaca decomposition. This resolves the invariance problem in the detailed Oaxaca decomposition. An algorithm to calculate an asymptoti...

OBJECTIVE To develop prediction equations for spirometry for children from northern India using current international guidelines for standardization. DESIGN Re-analysis of cross-sectional data from a single school. PARTICIPANTS 670 normal children (age 6-17 y; 365 boys) of northern Indian parentage. METHODS After screening for normal health, we carried out spirometry with recommended qual...

We consider estimation in a semiparametric generalized linear model for clustered data using estimating equations. Our results apply to the case where the number of observations per cluster is Ž nite, whereas the number of clusters is large. The mean of the outcome variable Œ is of the form g4Œ5 D X‚C ˆ4T 5, where g4¢5 is a link function, X and T are covariates, ‚ is an unknown parameter vector...

An earlier study of peak expiratory flow (PEF) in normal adults contained too few men aged over 55 and women aged over 65 for the regression equations to be used for prediction in older people. A subsequent study was therefore carried out on an additional 23 men and 29 women aged 55 or over who were lifelong non-smokers and satisfied the same strict criteria of normality that had been used in t...

We consider the problem of estimating a solution to (random) systems of equations that involve convex nonlinearities which has applications in machine learning and signal processing. Conventional estimators based on empirical risk minimization generally lead to non-convex programs that are often computationally intractable. We propose anchored regression, a new approach that utilizes an anchor ...

The analysis of data arising from environmental health studies which collect a large number of measures of exposure can benefit from using latent variable models to summarize exposure information. However, difficulties with estimation of model parameters may arise since existing fitting procedures for linear latent variable models require correctly specified residual variance structures for unb...

Symbolic regression has many successful applications in learning free-form regular equations from data. Trying to apply the same approach to differential equations is the logical next step: so far, however, results have not matched the quality obtained with regular equations, mainly due to additional constraints and dependencies between variables that make the problem extremely hard to tackle. ...

The estimation of gestational age (GA) on fetal remains can be an important forensic issue. Forensic specialists usually use reference tables and regression equations derived from reference collections, which are quite rare in what fetuses are concerned. Since these tools are mostly grounded on ultrasonographic measurements, which are known to differ from real bones measurements or are based on...

In the present study, regression equations between body and head length measurements for the broad-snouted caiman (Caiman latirostris) are presented. Age and sex are discussed as sources of variation for allometric models. Four body-length, fourteen head-length, and ten ratio variables were taken from wild and captive animals. With the exception of body mass, log-transformation did not improve ...

We report new body mass estimates for the North American Eocene primate Omomys carteri. These estimates are based on postcranial measurements and a variety of analytical methods, including bivariate regression, multiple regression, and principal components analysis (PCA). All body mass estimation equations show high coefficients of determination (R2), and some equations exhibit low prediction e...