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The impact of covariance misspecification in multivariate Gaussian mixtures on estimation and inference: an application to longitudinal modeling

Multivariate Gaussian mixtures are a class of models that provide a flexible parametric approach for the representation of heterogeneous multivariate outcomes. When the outcome is a vector of repeated measurements taken on the same subject, there is often ...

Collection, synthesis, and interpretation of evidence: a proof-of-concept study in COPD

We present a clinical proof-of-concept (PoC) study in chronic obstructive pulmonary disease with the objective of assessing the bronchodilatory effect of an experimental drug as compared with an active control treatment. In such an exploratory Phase II se ...

A scan statistic for identifying optimal risk windows in vaccine safety studies using self-controlled case series design

Abstract In the examination of the association between vaccines and rare adverse events after vaccination in postlicensure observational studies, it is challenging to define appropriate risk windows because prelicensure RCTs provide little insight on the t ...

Meta-analysis of randomised trials with a continuous outcome according to baseline imbalance and availability of individual participant data

We describe methods for meta-analysis of randomised trials where a continuous outcome is of interest, such as blood pressure, recorded at both baseline (pre treatment) and follow-up (post treatment). We used four examples for illustration, covering situat ...

Uncovering selection bias in case–control studies using Bayesian post-stratification

Case–control studies are particularly prone to selection bias, which can affect odds ratio estimation. Approaches to discovering and adjusting for selection bias have been proposed in the literature using graphical and heuristic tools as well as more comp ...

A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk

We describe a value-driven approach to optimizing pharmaceutical portfolios. Our approach incorporates inputs from research and development and commercial functions by simultaneously addressing internal and external factors. This approach differentiates i ...

Testing for improvement in prediction model performance

Authors have proposed new methodology in recent years for evaluating the improvement in prediction performance gained by adding a new predictor, Y, to a risk model containing a set of baseline predictors, X, for a binary outcome D. We prove theoretically ...

Interval-censored parametric regression survival models and the analysis of longitudinal trials

This paper develops interval censoring likelihood methods in the context of parametric proportional hazard (PH) and non-PH regression models in the longitudinal study setting to reanalyze the medical research council's randomized controlled trial of ...

Semiparametric transformation models for panel count data with correlated observation and follow-up times

The statistical analysis of panel count data has recently attracted a great deal of attention, and a number of approaches have been developed. However, most of these approaches are for situations where the observation and follow-up processes are independe ...

Semiparametric odds ratio model for case–control and matched case–control designs

We propose a semiparametric odds ratio model that extends Umbach and Weinberg's approach to exploiting gene–environment association model for efficiency gains in case–control designs to both discrete and continuous data. We directly model the gene–en ...

A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis

The use of individual participant data (IPD) from multiple studies is an increasingly popular approach when developing a multivariable risk prediction model. Corresponding datasets, however, typically differ in important aspects, such as baseline risk. Th ...

Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach

No one treatment is likely to affect all patients with a disorder in the same way. A treatment highly effective for some may be ineffective or even harmful for others. Statistically significant or not, the effect sizes of many treatments tend to be small. ...

Group sequential enrichment design incorporating subgroup selection

An important component of clinical trials in drug development is the analysis of treatment efficacy in patient subgroups (subpopulations). Because of concerns of multiplicity and of the small sample sizes often involved, such analyses can present substant ...

A Bayesian decision-theoretic sequential response-adaptive randomization design

We propose a class of phase II clinical trial designs with sequential stopping and adaptive treatment allocation to evaluate treatment efficacy. Our work is based on two-arm (control and experimental treatment) designs with binary endpoints. Our overall g ...

Multi-profile hidden Markov model for mood, dietary intake, and physical activity in an intervention study of childhood obesity

Motivated by an application to childhood obesity data in a clinical trial, this paper describes a multi-profile hidden Markov model (HMM) that uses several temporal chains of measures respectively related to psychosocial attributes, dietary intake, and en ...

Modeling time-varying effects with generalized and unsynchronized longitudinal data

We propose novel estimation approaches for generalized varying coefficient models that are tailored for unsynchronized, irregular and infrequent longitudinal designs/data. Unsynchronized longitudinal data refer to the time-dependent response and covariate ...

Dose-finding designs using a novel quasi-continuous endpoint for multiple toxicities

The aim of a phase I oncology trial is to identify a dose with an acceptable safety profile. Most phase I designs use the dose-limiting toxicity, a binary endpoint, to assess the unacceptable level of toxicity. The dose-limiting toxicity might be incomple ...

Erratum note to ‘Time-to-event analysis with treatment arm selection at interim’

22 January 2013 Erratum note to ‘Time-to-event analysis with treatment arm selection at interim’ ...

Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms

In this manuscript, we consider methods for the analysis of populations of electroencephalogram signals during sleep for the study of sleep disorders using hidden Markov models (HMMs). Notably, we propose an easily implemented method for simultaneously mo ...

Correction

24 January 2013 Correction ...

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