Statistical Methods in Medical Research This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits
Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components—one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce depe...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Neelon, B., Chang, H. H., Ling, Q., Hastings, N. S. Tags: Articles Source Type: research

Comparison of imputation variance estimators
Appropriate imputation inference requires both an unbiased imputation estimator and an unbiased variance estimator. The commonly used variance estimator, proposed by Rubin, can be biased when the imputation and analysis models are misspecified and/or incompatible. Robins and Wang proposed an alternative approach, which allows for such misspecification and incompatibility, but it is considerably more complex. It is unknown whether in practice Robins and Wang’s multiple imputation procedure is an improvement over Rubin’s multiple imputation. We conducted a critical review of these two multiple imputation approach...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Hughes, R., Sterne, J., Tilling, K. Tags: Articles Source Type: research

Bayesian inference for joint modelling of longitudinal continuous, binary and ordinal events
In medical studies, repeated measurements of continuous, binary and ordinal outcomes are routinely collected from the same patient. Instead of modelling each outcome separately, in this study we propose to jointly model the trivariate longitudinal responses, so as to take account of the inherent association between the different outcomes and thus improve statistical inferences. This work is motivated by a large cohort study in the North West of England, involving trivariate responses from each patient: Body Mass Index, Depression (Yes/No) ascertained with cut-off score not less than 8 at the Hospital Anxiety and Depression...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Li, Q., Pan, J., Belcher, J. Tags: Articles Source Type: research

Detecting the violation of variance homogeneity in mixed models
Mixed-effects models are increasingly used in many areas of applied science. Despite their popularity, there is virtually no systematic approach for examining the homogeneity of the random-effects covariance structure commonly assumed for such models. We propose two tests for evaluating the homogeneity of the covariance structure assumption across subjects: one is based on the covariance matrices computed from the fitted model and the other is based on the empirical variation computed from the estimated random effects. We used simulation studies to compare performances of the two tests for detecting violations of the homog...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Fang, X., Li, J., Wong, W. K., Fu, B. Tags: Articles Source Type: research

Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties
Competing risks data often exist within a center in multi-center randomized clinical trials where the treatment effects or baseline risks may vary among centers. In this paper, we propose a subdistribution hazard regression model with multivariate frailty to investigate heterogeneity in treatment effects among centers from multi-center clinical trials. For inference, we develop a hierarchical likelihood (or h-likelihood) method, which obviates the need for an intractable integration over the frailty terms. We show that the profile likelihood function derived from the h-likelihood is identical to the partial likelihood, and...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Ha, I. D., Christian, N. J., Jeong, J.-H., Park, J., Lee, Y. Tags: Articles Source Type: research

Joint modeling of HIV data in multicenter observational studies: A comparison among different approaches
Disease process over time results from the combination of event history information and longitudinal process. Commonly, separate analyses of longitudinal and survival outcomes are performed. However, discharging the dependence between these components may cause misleading results. Separate analyses are difficult to interpret whenever one deals with observational retrospective multicenter cohort studies where the biomarkers are poorly monitored over time, while the survival component may be affected by several sources of bias, such as multiple endpoints, multiple time-scales, and informative censoring. We discuss how joint ...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Brombin, C., Di Serio, C., Rancoita, P. M. Tags: Articles Source Type: research

Optimal scheduling of post-therapeutic follow-up of patients treated for cancer for early detection of relapses
Post-therapeutic surveillance is one important component of cancer care. However, there still is no evidence-based strategies to schedule patients’ follow-up examinations. Our approach is based on the modeling of the probability of the onset of relapse at an early asymptotic or preclinical stage and its transition to a clinical stage. For that we consider a multistate homogeneous Markov model, which includes the natural history of relapse. The model also handles separately the different types of possible relapses. The optimal schedule is provided by the calendar visit that maximizes a utility function. The methodolog...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Somda, S. M., Leconte, E., Boher, J.-M., Asselain, B., Kramar, A., Filleron, T. Tags: Articles Source Type: research

On a class of optimal covariate-adjusted response adaptive designs for survival outcomes
A class of optimal covariate-adjusted response adaptive procedures is developed for phase III clinical trials when the treatment response is a survival time and there is random censoring. The basic aim is to develop an allocation design by combining the ethical aspects with statistical precision in a reasonable way under the presence of covariate information. Considering minimisation of total hazards as the ethical requirement, the proposed procedure is assessed in terms of the assignment to the better treatment and the efficiency (i.e. power) to detect a small departure in treatment effectiveness. The applicability of the...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Biswas, A., Bhattacharya, R., Park, E. Tags: Articles Source Type: research

A cautionary note on the use of attributable fractions in cohort studies
The attributable fraction is a widely used measure to quantify the public health impact of an exposure on an outcome. It was originally proposed for binary outcomes, but attributable fraction estimators have also been proposed for time-to-event outcomes. In this note, we consider an estimator which was proposed by Benichou (Stats Methods Med Res, 2001) and is supposed to estimate the cohort attributable fraction, i.e. the number of events that would have been prevented in the cohort during follow-up, if the exposure would hypothetically have been eliminated. We show that this estimator is only valid under certain assumptio...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Sjölander, A. Tags: Articles Source Type: research

Optimal selection of individuals for repeated covariate measurements in follow-up studies
Repeated covariate measurements bring important information on the time-varying risk factors in long epidemiological follow-up studies. However, due to budget limitations, it may be possible to carry out the repeated measurements only for a subset of the cohort. We study cost-efficient alternatives for the simple random sampling in the selection of the individuals to be remeasured. The proposed selection criteria are based on forms of the D-optimality. The selection methods are compared with the simulation studies and illustrated with the data from the East–West study carried out in Finland from 1959 to 1999. The res...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Reinikainen, J., Karvanen, J., Tolonen, H. Tags: Articles Source Type: research

Survival analysis with functional covariates for partial follow-up studies
This article studies a new class of functional survival models where the covariates are only monitored in a time interval that is shorter than the whole follow-up period. This paper is motivated by the analysis of a longitudinal study on advanced myeloma patients who received stem cell transplants and T cell infusions after the transplants. The absolute lymphocyte cell counts were collected serially during hospitalization. Those patients are still followed up if they are alive after hospitalization, while their absolute lymphocyte cell counts cannot be measured after that. Another complication is that absolute lymphocyte c...
Source: Statistical Methods in Medical Research - November 15, 2016 Category: Statistics Authors: Fang, H.-B., Wu, T. T., Rapoport, A. P., Tan, M. Tags: Articles Source Type: research

Werner Vack, Regression models as a tool in medical research
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Allgar, V. Tags: Book reviews Source Type: research

Newcombe RG, Confidence intervals for proportions and related measures of effect size
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Hayes, K. Tags: Book reviews Source Type: research

Lee, M. P. (2012). Bayesian Statistics: An Introduction
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Ruggeri, F. Tags: Book reviews Source Type: research

Dan Mayer, Essential evidence-based medicine. 2nd edn
(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Oke, J. Tags: Book reviews Source Type: research