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

Accounting for perception, placebo and unmasking effects in estimating treatment effects in randomised clinical trials
There is a rich literature on the role of placebos in experimental design and evaluation of therapeutic agents or interventions. The importance of masking participants, investigators and evaluators to treatment assignment (treatment or placebo) has long been stressed as a key feature of a successful trial design. Nevertheless, there is considerable variability in the technical definition of the placebo effect and the impact of treatment assignments being unmasked. We suggest a formal concept of a ‘perception effect’ and define unmasking and placebo effects in the context of randomised trials. We employ modern t...
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Jamshidian, F., Hubbard, A. E., Jewell, N. P. Tags: Articles Source Type: research

Testing for seasonality using circular distributions based on non-negative trigonometric sums as alternative hypotheses
In medical and epidemiological studies, the importance of detecting seasonal patterns in the occurrence of diseases makes testing for seasonality highly relevant. There are different parametric and non-parametric tests for seasonality. One of the most widely used parametric tests in the medical literature is the Edwards test. The Edwards test considers a parametric alternative that is a sinusoidal curve with one peak and one trough. The Cave and Freedman test is an extension of the Edwards test that is also frequently applied and considers a sinusoidal curve with two peaks and two troughs as the alternative hypothesis. The...
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Fernandez-Duran, J. J., Gregorio-Dominguez, M. M. Tags: Articles Source Type: research

Estimating overall exposure effects for zero-inflated regression models with application to dental caries
Zero-inflated (ZI) models, which may be derived as a mixture involving a degenerate distribution at value zero and a distribution such as negative binomial (ZINB), have proved useful in dental and other areas of research by accommodating ‘extra’ zeroes in the data. Used in conjunction with generalised linear models, they allow covariate-adjusted inference of an exposure effect on the mixing probability and on the mean for the non-degenerate distribution. However, these models do not directly provide covariate-adjusted inference for the overall exposure effect. Focusing on the ZINB and ZI beta binomial models, w...
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Albert, J. M., Wang, W., Nelson, S. Tags: Articles Source Type: research

A multi-state model for the analysis of changes in cognitive scores over a fixed time interval
In this article, we present the novel approach of using a multi-state model to describe longitudinal changes in cognitive test scores. Scores are modelled according to a truncated Poisson distribution, conditional on survival to a fixed endpoint, with the Poisson mean dependent upon the baseline score and covariates. The model provides a unified treatment of the distribution of cognitive scores, taking into account baseline scores and survival. It offers a simple framework for the simultaneous estimation of the effect of covariates modulating these distributions, over different baseline scores. A distinguishing feature is ...
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Mitnitski, A. B., Fallah, N., Dean, C. B., Rockwood, K. Tags: Articles Source Type: research

On the power of the Cochran-Armitage test for trend in the presence of misclassification
This article provides a unified approach to determination of the power function over different sampling strategies (fixed overall sample size or fixed marginal sample sizes) and allowing for misclassification in one or both variables. The misclassification may be either differential or non-differential. In addition to the standard CA test, results are also given which provide some insight into the performance of the modified CA test, which utilizes a standard error obtained without invoking the null hypothesis. Even without misclassification, some new expressions are also obtained for determining power with a fixed overall...
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Buonaccorsi, J. P., Laake, P., Veierod, M. B. Tags: Articles Source Type: research

Modelling batched Gaussian longitudinal weight data in mice subject to informative dropout
This article focuses on modelling such longitudinal data when the outcome at each follow-up time is collected in batches rather than individually collected. The problem occurred in a study that compared the weight of mice over time between a control and a treatment group, where animal weight was measured in batches of five animals per cage. We develop both a shared parameter and a pattern mixture modelling approach for accounting for potentially informative dropout due to an animal's death. Our methodology suggests that animals receiving the treatment have a lower weight in mid-life, and have a slower decline in weight in ...
Source: Statistical Methods in Medical Research - May 16, 2014 Category: Statistics Authors: Albert, P. S., Shih, J. H. Tags: Articles Source Type: research

Prior choice in discrete latent modeling of spatially referenced cancer survival
In this article, we examine the development and use of covariate models where the relation with explanantory covariates is spatially adaptive. In this way space is regarded as an effect modifier. We examine the possibility of discrete groupings of coefficients (clustering of coefficients). Our application is to prostate cancer survival based on the SEER cancer registry for the state of Louisiana, USA. This registry holds individual records linked to vital outcomes and is geo-coded at county level. We examine a range of potential prior distributions for groupings of regression coefficients in application to these data. (Sou...
Source: Statistical Methods in Medical Research - March 20, 2014 Category: Statistics Authors: Lawson, A. B., Choi, J., Zhang, J. Tags: Articles Source Type: research

Interpolation between spatial frameworks: An application of process convolution to estimating neighbourhood disease prevalence
Health data may be collected across one spatial framework (e.g. health provider agencies), but contrasts in health over another spatial framework (neighbourhoods) may be of policy interest. In the UK, population prevalence totals for chronic diseases are provided for populations served by general practitioner practices, but not for neighbourhoods (small areas of circa 1500 people), raising the question whether data for one framework can be used to provide spatially interpolated estimates of disease prevalence for the other. A discrete process convolution is applied to this end and has advantages when there are a relatively...
Source: Statistical Methods in Medical Research - March 20, 2014 Category: Statistics Authors: Congdon, P. Tags: Articles Source Type: research

Spatial health effects analysis with uncertain residential locations
Spatial epidemiology has benefited greatly from advances in geographic information system technology, which permits extensive study of associations between various health responses and a wide array of socio-economic and environmental factors. However, many spatial epidemiological datasets have missing values for a substantial proportion of spatial variables, such as the census tract of residence of study participants. The standard approach is to discard these observations and analyze only complete observations. In this article, we propose a new hierarchical Bayesian spatial model to handle missing observation locations. Ou...
Source: Statistical Methods in Medical Research - March 20, 2014 Category: Statistics Authors: Reich, B. J., Chang, H. H., Strickland, M. J. Tags: Articles Source Type: research

On identification in Bayesian disease mapping and ecological-spatial regression models
We discuss identification of structural characteristics of the underlying relative risks ensemble for posterior relative risks inference within Bayesian generalized linear mixed model framework for small-area disease mapping and ecological–spatial regression. We revisit conditionally specified and locally characterized Gaussian Markov random field risks ensemble priors in univariate disease mapping and communicate insight into Gaussian Markov random field variance–covariance characteristics for representing disease risks variability and spatial risks interactions and for structural identification with respect t...
Source: Statistical Methods in Medical Research - March 20, 2014 Category: Statistics Authors: MacNab, Y. C. Tags: Articles Source Type: research

A spatial bivariate probit model for correlated binary data with application to adverse birth outcomes
Motivated by a study examining geographic variation in birth outcomes, we develop a spatial bivariate probit model for the joint analysis of preterm birth and low birth weight. The model uses a hierarchical structure to incorporate individual and areal-level information, as well as spatially dependent random effects for each spatial unit. Because rates of preterm birth and low birth weight are likely to be correlated within geographic regions, we model the spatial random effects via a bivariate conditionally autoregressive prior, which induces regional dependence between the outcomes and provides spatial smoothing and shar...
Source: Statistical Methods in Medical Research - March 20, 2014 Category: Statistics Authors: Neelon, B., Anthopolos, R., Miranda, M. L. Tags: Articles Source Type: research

Special Issue on Spatial Methods for Health Policy Research
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - March 20, 2014 Category: Statistics Authors: Neelon, B., Lawson, A. B. Tags: Editorial Source Type: research