Bartlett corrections in Birnbaum-Saunders nonlinear regression models

Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.

Estimate of corrected values and the effect of correction for measurement error in dietary data obtained by the Food Frequency Questionnaire for Adolescents (AFFQ)

The scope of this study was to estimate calibrated values for dietary data obtained by the Food Frequency Questionnaire for Adolescents (FFQA) and illustrate the effect of this approach on food consumption data. The adolescents were assessed on two occasions, with an average interval of twelve months. In 2004, 393 adolescents participated, and 289 were then reassessed in 2005. Dietary data obtained by the FFQA were calibrated using the regression coefficients estimated from the average of two 24-hour recalls (24HR) of the subsample. The calibrated values were similar to the the 24HR reference measurement in the subsample. In 2004 and 2005 a significant difference was observed between the average consumption levels of the FFQA before and after calibration for all nutrients. With the use of calibrated data the proportion of schoolchildren who had fiber intake below the recommended level increased. Therefore, it is seen that calibrated data can be used to obtain adjusted associations due to reclassification of subjects within the predetermined categories.

Validation of the MAPGEO2010 and comparison with recent geopotential models

This paper presents the offorts to calculate the geoid model for Brazil. It is limited by 6 degrees N and 35 degrees S in latitude and 30 degrees W and 75 degrees W in longitude. The terrestrial gravity data for the continent have been updated by means of the most recent surveys in Brazil and in the neighbour countries. The complete Bouguer and Helmert gravity anomalies have been derived through the Canadian package SHGEO. The short wavelength component was estimated via FFT. The geopotential model EGM2008 was used as a reference field restricted to degree and order 150. The model was validated over 844 GPS observations on Bench Marks of the spirit leveling network. The height anomalies plus a topography dependent correction term derived from EGM2008 (degree 2190 and order 2159), GO_CONS_GCF_2_DIR_R2 (degree and order 240), GOCO02S (degree and order 250), EIGEN 51C (degree and order 359) and EIGEN 6C (degree and order 1420), geoidal height derived from MAPGEO2004 (old official geoid model in Brazil) have also been compared to the GPS points on Bench Marks.

On Wald Residuals in Generalized Linear Models

A rigorous asymptotic theory for Wald residuals in generalized linear models is not yet available. The authors provide matrix formulae of order O(n(-1)), where n is the sample size, for the first two moments of these residuals. The formulae can be applied to many regression models widely used in practice. The authors suggest adjusted Wald residuals to these models with approximately zero mean and unit variance. The expressions were used to analyze a real dataset. Some simulation results indicate that the adjusted Wald residuals are better approximated by the standard normal distribution than the Wald residuals.