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- Luís Meira-Machado, Carmen Cadarso-Suárez, Francisco Gude, Artur Araújo
- Comp. Math. Methods in Medicine
- 2013

The Cox proportional hazards regression model has become the traditional choice for modeling survival data in medical studies. To introduce flexibility into the Cox model, several smoothing methods may be applied, and approaches based on splines are the most frequently considered in this context. To better understand the effects that each continuous… (More)

- Luís Meira-Machado, Jacobo de Uña-Alvarez, Carmen Cadarso-Suárez
- Lifetime data analysis
- 2006

In this paper we consider nonparametric estimation of transition probabilities for multi-state models. Specifically, we focus on the illness-death or disability model. The main novelty of the proposed estimators is that they do not rely on the Markov assumption, typically assumed to hold in a multi-state model. We investigate the asymptotic properties of… (More)

- Luís Meira-Machado, Jacobo de Uña-Alvarez, Carmen Cadarso-Suárez, Per K Andersen
- Statistical methods in medical research
- 2009

The experience of a patient in a survival study may be modelled as a process with two states and one possible transition from an "alive" state to a "dead" state. In some studies, however, the "alive" state may be partitioned into two or more intermediate (transient) states, each of which corresponding to a particular stage of the illness. In such studies,… (More)

- Luís Meira-Machado, Carmen Cadarso-Suárez, Jacobo de Uña-Álvarez
- Computer Methods and Programs in Biomedicine
- 2007

The aim of this paper is to present an R library, called tdc.msm, developed to analyze multi-state survival data. In this library, the time-dependent regression model and multi-state models are included as two possible approaches for such data. For the multi-state modelling five different models are considered, allowing the user to choose between Markov and… (More)

- CATHOLIQUE DE LOUVAIN, Ingrid Van Keilegom, Jacobo de Uña-Álvarez, Luis Meira-Machado
- 2008

Let (T 1 , T 2) be gap times corresponding to two consecutive events, which are observed subject to random right-censoring, and suppose the vector (T 1 , T 2) satisfies the nonparametric location-scale regression model T 2 = m(T 1) + σ(T 1)ε, where the functions m and σ are 'smooth', and ε is independent of T 1. The aim of this paper is twofold. First, we… (More)

- Luís Meira-Machado, Susana Faria
- Communications in Statistics - Simulation and…
- 2014

- C. Moreira, Jacobo de Uña-Álvarez, Luís Meira-Machado
- Computational Statistics & Data Analysis
- 2016

- Jacobo de Uña-Álvarez, Luís Meira-Machado
- Biometrics
- 2015

Multi-state models are often used for modeling complex event history data. In these models the estimation of the transition probabilities is of particular interest, since they allow for long-term predictions of the process. These quantities have been traditionally estimated by the Aalen-Johansen estimator, which is consistent if the process is Markov.… (More)

- Artur Araújo, Luís Meira-Machado, Javier Roca-Pardiñas, Lúıs Meira-Machado
- 2013

One major goal in clinical applications of multi-state models is the estimation of transition probabilities. The usual nonparametric estimator of the transition matrix for non-homogeneous Markov processes is the Aalen-Johansen estimator (Aalen and Johansen [1]). However, two problems may arise from using this estimator: first, its standard error may be… (More)

- Luís Meira-Machado, Jacobo de Uña-Álvarez, Somnath Datta, Lúıs Meira-Machado
- 2011

One important goal in multi-state modeling is the estimation of transition probabilities. In longitudinal medical studies these quantities are particularly of interest since they allow for long-term predictions of the process. In recent years significant contributions have been made regarding this topic. However, most of the approaches assume independent… (More)