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On fitting spatio-temporal disease mapping models using approximate Bayesian inference
Spatio-temporal disease mapping comprises a wide range of models used to describe the distribution of a disease in space and its evolution in time. These models have been commonly formulated within a hierarchical Bayesian framework with two main approaches: an empirical Bayes (EB) and a fully Bayes (FB) approach. The EB approach provides point estimates of the parameters relying on the well-known penalized quasi-likelihood (PQL) technique. The FB approach provides the posterior distribution of the target parameters. These marginal distributions are not usually available in closed form and common estimation procedures are b...
Source: Statistical Methods in Medical Research - November 18, 2014 Category: Statistics Authors: Ugarte, M. D., Adin, A., Goicoa, T., Militino, A. F. Tags: Articles Source Type: research

Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies
Estimating the long-term health impact of air pollution using an ecological spatio-temporal study design is a challenging task, due to the presence of residual spatio-temporal autocorrelation in the health counts after adjusting for the covariate effects. This autocorrelation is commonly modelled by a set of random effects represented by a Gaussian Markov random field (GMRF) prior distribution, as part of a hierarchical Bayesian model. However, GMRF models typically assume the random effects are globally smooth in space and time, and thus are likely to be collinear to any spatially and temporally smooth covariates such as ...
Source: Statistical Methods in Medical Research - November 18, 2014 Category: Statistics Authors: Lee, D., Mitchell, R. Tags: Articles Source Type: research

GEOMED 2013 Editorial
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - November 18, 2014 Category: Statistics Tags: Editorial Source Type: research

Interpretation of patient-reported outcomes
This article provides an update review on two broad approaches – anchor-based and distributed-based – aimed at enhancing the understanding and meaning of patient-reported outcome scores. Anchor-based approaches include percentages based on thresholds, criterion-group interpretation, content-based interpretation, and clinical important difference. Distributed-based approaches include effect size, probability of relative benefit, and responder analysis and cumulative proportions. A third strategy called mediation analysis, which can elucidate a health condition measured by a patient-reported outcome in the contex...
Source: Statistical Methods in Medical Research - September 24, 2014 Category: Statistics Authors: Cappelleri, J. C., Bushmakin, A. G. Tags: Articles Source Type: research

Practical and statistical issues in missing data for longitudinal patient-reported outcomes
Patient-reported outcomes are increasingly used in health research, including randomized controlled trials and observational studies. However, the validity of results in longitudinal studies can crucially hinge on the handling of missing data. This paper considers the issues of missing data at each stage of research. Practical strategies for minimizing missingness through careful study design and conduct are given. Statistical approaches that are commonly used, but should be avoided, are discussed, including how these methods can yield biased and misleading results. Methods that are valid for data which are missing at rand...
Source: Statistical Methods in Medical Research - September 24, 2014 Category: Statistics Authors: Bell, M. L., Fairclough, D. L. Tags: Articles Source Type: research

Estimating effect sizes for health-related quality of life outcomes
To enable an assessment of the costs and benefits of a new health technology one should use a range of outcome measures, including medical, psychosocial and economic. Therefore, unless a patient-reported outcome as well as clinical outcome is assessed in a study, the effect of a health technology on the patient will remain unknown as two therapies may have similar clinical consequences but different impacts upon the quality of the life of the patients. An important issue when designing a study with a new patient-reported outcome is the quantification of an effect size. Through a case study we highlight how simple calculati...
Source: Statistical Methods in Medical Research - September 24, 2014 Category: Statistics Authors: Julious, S. A., Walters, S. J. Tags: Articles Source Type: research

A general theoretical framework for interpreting patient-reported outcomes estimated from ordinally scaled item responses
A simple theoretical framework explains patient responses to items in rating scale questionnaires. Fixed latent variables position each patient and each item on the same linear scale. Item responses are governed by a set of fixed category thresholds, one for each ordinal response category. A patient’s item responses are magnitude estimates of the difference between the patient variable and the patient’s estimate of the item variable, relative to his/her personally defined response category thresholds. Differences between patients in their personal estimates of the item variable and in their personal choices of ...
Source: Statistical Methods in Medical Research - September 24, 2014 Category: Statistics Authors: Massof, R. W. Tags: Articles Source Type: research

Statistical challenges in drug approval trials that use patient-reported outcomes
This article describes challenging aspects of the use of patient-reported outcome instruments in clinical trials for drug approval, in our perspective as statistical reviewers at the US Food and Drug Administration. We discuss aspects of planning and interpreting results in clinical trials (1) adapting an existing patient-reported outcome instrument for use in clinical trials, (2) using multi-item patient-reported outcomes and (3) missing patient-reported outcome values from many subjects over time. These challenges are illustrated with multiple examples from different clinical trials for different indications. We finally ...
Source: Statistical Methods in Medical Research - September 24, 2014 Category: Statistics Authors: Izem, R., Kammerman, L. A., Komo, S. Tags: Articles Source Type: research

Statistical considerations in the design, analysis and interpretation of clinical studies that use patient-reported outcomes
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - September 24, 2014 Category: Statistics Authors: Kammerman, L. A., Grosser, S. Tags: Editorial Source Type: research

Methods to obtain referral criteria in growth monitoring
An important goal of growth monitoring is to identify genetic disorders, diseases or other conditions that manifest themselves through an abnormal growth. The two main conditions that can be detected by height monitoring are Turner’s syndrome and growth hormone deficiency. Conditions or risk factors that can be detected by monitoring weight or body mass index include hypernatremic dehydration, celiac disease, cystic fibrosis and obesity. Monitoring infant head growth can be used to detect macrocephaly, developmental disorder and ill health in childhood. This paper describes statistical methods to obtain evidence-base...
Source: Statistical Methods in Medical Research - July 15, 2014 Category: Statistics Authors: van Dommelen, P., van Buuren, S. Tags: Articles Source Type: research

Growth charts of human development
This article reviews and compares two types of growth charts for tracking human development over age. Both charts assume the existence of a continuous latent variable, but relate to the observed data in different ways. The D-score diagram summarizes developmental indicators into a single aggregate score measuring global development. The relations between the indicators should be consistent with the Rasch model. If true, the D-score is a measure with interval scale properties, and allows for the calculation of meaningful differences both within and across age. The stage line diagram describes the natural development of ordi...
Source: Statistical Methods in Medical Research - July 15, 2014 Category: Statistics Authors: van Buuren, S. Tags: Articles Source Type: research

Modeling height for children born small for gestational age treated with growth hormone
The analysis of growth curves of children can be done on either the original scale or in standard deviation scores. The first approach is found in many statistical textbooks, while the second approach is common in endocrinology, for instance in the evaluation of the effect of growth hormone in children that are born small for gestational age that remain small later in childhood. We illustrate here that the second approach may involve more complex modeling and hence a worse model fit. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - July 15, 2014 Category: Statistics Authors: Willemsen, S. P., de Ridder, M., Eilers, P. H. C., Hokken-Koelega, A., Lesaffre, E. Tags: Articles Source Type: research

Automatic smoothing parameter selection in GAMLSS with an application to centile estimation
A method for automatic selection of the smoothing parameters in a generalised additive model for location, scale and shape (GAMLSS) model is introduced. The method uses a P-spline representation of the smoothing terms to express them as random effect terms with an internal (or local) maximum likelihood estimation on the predictor scale of each distribution parameter to estimate its smoothing parameters. This provides a fast method for estimating multiple smoothing parameters. The method is applied to centile estimation where all four parameters of a distribution for the response variable are modelled as smooth functions of...
Source: Statistical Methods in Medical Research - July 15, 2014 Category: Statistics Authors: Rigby, R. A., Stasinopoulos, D. M. Tags: Articles Source Type: research

Editorial
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - July 15, 2014 Category: Statistics Authors: Eilers, P. H. Tags: Editorial Source Type: research

Response: Did Newton-Raphson really fail?
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Meng, X.-L. Tags: Letter and Response Source Type: research