Rolando De la Cruz

Universidad Adolfo Ibáñez · Facultad de Ingeniería y Ciencias

Mixture cure rate models have been developed to analyze failure time data where a proportion never fails. For such data, standard survival models are usually not appropriate because they do not account for the possibility of non-failure. In this context, mixture cure rate models assume that the studied population is a mixture of susceptible subject...

Araucanian herring, Strangomera bentincki, is ecologically and economically important. Its complexity, like that of other pelagic fish, arises from seasonal population changes related to distribution with different spatial dynamics and demographic fractions, subject to strong environmental and fishing exploitation variations. This implies the neces...

Across several medical fields, developing an approach for disease classification is an important challenge. The usual procedure is to fit a model for the longitudinal response in the healthy population, a different model for the longitudinal response in the diseased population, and then apply Bayes’ theorem to obtain disease probabilities given the...

This study aims to analyze and explore criminal recidivism with different modeling strategies: one based on an explanation of the phenomenon and another based on a prediction task. We compared three common statistical approaches for modeling recidivism: the logistic regression model, the Cox regression model, and the cure rate model. The parameters...

Across several medical fields, developing an approach for disease classification is an important challenge. The usual procedure is to fit a model for the longitudinal response in the healthy population, a different model for the longitudinal response in disease population, and then apply the Bayes' theorem to obtain disease probabilities given the...

We propose a semiparametric nonlinear mixed-effects model (SNMM) using penalized splines to classify longitudinal data and improve the prediction of a binary outcome. The work is motivated by a study in which different hormone levels were measured during the early stages of pregnancy, and the challenge is using this information to predict normal ve...

Consider longitudinal observations across different subjects such that the underlying distribution is determined by a non-linear mixed-effects model. In this context, we look at the misclassification error rate for allocating future subjects using cross-validation, bootstrap algorithms (parametric bootstrap, leave-one-out, .632 and [Formula]), and...

Objective: To compare early child development and associated factors at baseline in pre-school children from public and private health sectors. Patients and method: The sample consisted of 1045 children aged 30-58 months, 52% male, and 671 from the public and 380 from the private sector of the metropolitan region in Chile were evaluated using Ba...

Background Maule Cohort (MAUCO), a Chilean cohort study, seeks to analyze the natural history of chronic diseases in the agricultural county of Molina (40,000 inhabitants) in the Maule Region, Chile. Molina´s population is of particular interest because in the last few decades it changed from being undernourished to suffering excess caloric intake,...

We propose a classification method for longitudinal data. The Bayes classifier is classically used to determine a classification rule where the underlying density in each class needs to be well modeled and estimated. This work is motivated by a real dataset of hormone levels measured at the early stages of pregnancy that can be used to predict norm...

Introduction: Febrile neutropenia (FN) is a common complication of patients undergoing chemotherapy (QMT). Clinical presentation is varied, from mild fever to severe sepsis with invasive bacterial infection (IBI) or invasive fungal infection (IFI), with great impact on prognosis and patient mortality. Patients and methods: Prospective cohort stu...

Medical care provided by medical specialists is one of the scarcest resources in the public system. It is costly and difficult to access for the general population. Availability and accessibility of specialized care is related to economic, social and cultural aspects that vary among geographical areas. An aggravating factor for this situation is pa...

A common assumption in nonlinear mixed-effects models is the normality of both random effects and within-subject errors. However, such assumptions make inferences vulnerable to the presence of outliers. More flexible distributions are therefore necessary for modeling both sources of variability in this class of models. In the present paper, I consi...

Joint models for a wide class of response variables and longitudinal measurements consist on a mixed-effects model to fit longitudinal trajectories whose random effects enter as covariates in a generalized linear model for the primary response. They provide a useful way to asses association between these two kinds of data, which in clinical studies...

Nonlinear mixed-effects models are very useful to analyze repeated measures data and are used in a variety of applications. Normal distributions for random effects and residual errors are usually assumed, but such assumptions make inferences vulnerable to the presence of outliers. In this work, we introduce an extension of a normal nonlinear mixed-...

Most Chagas patients belong to the chronic indeterminate stage, in which pharmacological treatment has an inconclusive outcome. To evaluate the efficacy of nifurtimox treatment in chronic asymptomatic Trypanosoma cruzi infection. We performed a systematic review and meta-analysis of electronically published literature, with no language, type of stu...

Introducción: La mayoría de los pacientes con enfermedad de Chagas se encuentran en fase crónica indeterminada donde los resultados de tratamiento farmacológico no han sido concluyentes. Objetivo: Evaluar la evidencia que apoya la eicacia del tratamiento con nifurtimox en la infección crónica por Trypanosoma cruzi asintomática. Método: Revisión sis...

In many studies, the association of longitudinal measurements of a continuous response and a binary outcome are often of interest. A convenient framework for this type of problems is the joint model, which is formulated to investigate the association between a binary outcome and features of longitudinal measurements through a common set of latent r...

Introduction: The melanocortin system plays an important role in energy homeostasis. Mice genetically deficient in the melanocortin-3 receptor gene have a normal body weight with increased body fat, mild hypophagia compared to wild-type mice. In humans, Thr6Lys and Val81Ile variants of the melanocortin-3 receptor gene (MC3R) have been associated w...

This paper considers the three-parameter family of symmetric unimodal circular distributions proposed by Batschelet in [1], an extension of the von Mises distribution containing distributional forms ranging from the highly leptokurtic to the very platykurtic. The family's fundamental properties are given, and likelihood-based techniques described w...

Generalized linear mixed models form a general class of random effects models for discrete and continuous response in the exponential family. Spatial GLMM are an extension of such models that allows us to fit spatial-dependent data. A popular model in this class is the probit-normal model. In this study we develop a novel exact algorithm to estimate...

Context: The effects of medical and surgical treatments for obesity on peptide YY (PYY) levels, in patients with similar weight loss, remain unclear. Objective: The objective of the study was to assess PYY and appetite before and after Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG), and medical treatment (MED). Design: This was a pro...

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multipl...

Typically, the fundamental assumption in non-linear regression models is the normality of the errors. Even though this model offers great flexibility for modeling these effects, it suffers from the same lack of robustness against departures from distributional assumptions as other statistical models based on the Gaussian distribution. It is of prac...

Multiple outcomes are often used to properly characterize an effect of interest. This article discusses model-based statistical methods for the classification of units into one of two or more groups where, for each unit, repeated measurements over time are obtained on each outcome. We relate the observed outcomes using multivariate nonlinear mixed-...

A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hierarchical models leading to a mixture of hierarchical models. We study both frequentist and Bayesian estimation procedures. From a classical viewpoint, we discuss maximum l...

This paper discusses Bayesian statistical methods for the classification of observations into two or more groups based on hierarchical models for nonlinear longitudinal profiles. Parameter estimation for a discriminant model that classifies individuals into distinct predefined groups or populations uses appropriate posterior simulation schemes. The...

We analyse data from a study involving 173 pregnant women. The data are observed values of the β human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six longitudinal responses for each woman. The main objective in this study is to predict normal versus abnormal pregnancy outcomes from...

The use of random-effects models for the analysis of longitudinal data with missing responses has been discussed by several authors. In this paper, we extend the non-linear random-effects model for a single response to the case of multiple responses, allowing for arbitrary patterns of observed and missing data. Parameters for this model are estimat...

Measurements on subjects in longitudinal medical studies are often collected at several different times or under different experimental conditions. Such multiple observations on the same subject generally produce serially correlated outcomes. Traditional regression methods assume that observations within subjects are independent which is not true i...

In this paper we develop a Bayesian analysis for the nonlinear regression model with errors that follow a continuous autoregressive process. In this way, unequally spaced observations do not present a problem in the analysis. We employ the Gibbs sampler, (see Gelfand, A., Smith, A. (199010. Gelfand , A. and Smith , A. 1990. Sampling based approac...

In many studies the association of longitudinal measurements of a continuous response and a primary endpoint are often of interest. A convenient fr amework for this type of prob- lems is joint models, which are formulated to investigate th e association between a primary endpoint and features of longitudinal measurements through a common set of lat...