Transformations to additivity for binary data

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Most Likely Transformations

We propose and study properties of maximum likelihood estimators in the class of conditional transformation models. Based on a suitable explicit parameterisation of the unconditional or conditional transformation function, we establish a cascade of increasingly complex transformation models that can be estimated, compared and analysed in the maximum likelihood framework. Models for the unconditional or conditional distribution function of any univariate response variable can be set-up and estimated in the same theoretical and computational framework simply by choosing an appropriate transformation function and parameterisation thereof. The ability to evaluate the distribution function directly allows us to estimate models based on the exact likelihood, especially in the presence of random censoring or truncation. For discrete and continuous responses, we establish the asymptotic normality of the proposed estimators. A reference software implementation of maximum likelihood-based estimation for conditional transformation models allowing the same flexibility as the theory developed here was employed to illustrate the wide range of possible applications.Comment: Accepted for publication by the Scandinavian Journal of Statistics 2017-06-1

Una formulación liofilizada para la preparación de Lys27(99MTc-EDDA/HYNIC)-Exendin(9-39)/99MTc-EDDA/HYNIC-TYR3-Octreótido para de-tectar insulinomas benignos y malignos

Los insulinomas son tumores pequeños con síntomas severos de hiperinsulinemia que pueden resultar en daños cerebrales permanentes si no se tratan de ma-nera temprana. Son muy difíciles de detectar por métodos convencionales. El tratamiento de elección es la cirugía, por lo que es necesaria su adecuada localización preoperatoria. Aproximadamente 90% de los insulinomas son benignos y sobre-expresan receptores del péptido tipo 1 análogo del glucagón (GLP-1R) y bajos niveles de receptores de somatosta-tina (SSTR)

Modeling repeated ordinal responses using a family of power transformations: application to neonatal hypothermia data

BACKGROUND: For analyzing a repeated ordinal response, it is common to use a multivariate cumulative logit model. This model may fit poorly, especially when a nonsymmetric response is available. In these cases, alternative strategies should be utilized. METHODS: In this paper, we present a family of power transformations for the cumulative probabilities to model asymmetric departures from the random-intercept cumulative logit model. To illustrate this method, we analyze the data from an epidemiologic study to identify risk factors of hypothermia among newly born infants in some referral university hospitals in Tehran, Iran. RESULTS: For hypothermia data, using this family of transformations and comparing the goodness-of-fit statistics showed that a model with the cumulative complementary log-log link gives us a better fit compared to a model with the cumulative logit link. CONCLUSION: In some areas, using the ordinary cumulative logit link function does not lead to the best fit. So, other link functions should be evaluated to discover the best transformation for the cumulative probabilities

Transformations to additivity for binary data

SIGLEAvailable from British Library Document Supply Centre- DSC:D34053/81 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Short-Term Projections of AIDS Cases in Mexico

We attempt to analyze and predict the behavior of the AIDS epidemic in Mexico. The reporting delay is corrected by using a cluster analysis, and the corrected data are used to make short-term projections by extrapolation, by fitting linear and log-linear models, and by back-calculation. The incubation period is assumed to have a Weibull distribution, and step functions are used for the infection functions. Most of the methods predict a mean of 25,000 accumulated cases by the end of 1993, and a comparison of the predictions with actual data up to November 1990 shows good agreement in all cases except the log-transformation linear model. The data for 1990 also show the reporting delay correction to be adequate in most cases