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(Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Tags: Articles Source Type: research

Non-Gaussian Berkson errors in bioassay
The experimental design plays an important role in every experimental study. However, if errors in the settings of the studied factors cannot be avoided, i.e. Berkson errors occur, the estimates of the model parameters may be biased and the variability in the study increased. Correction methods for the effect of Berkson errors are compared. The emphasis is on the study of correlated Berkson errors which follow non-Gaussian distribution as this appears to have been a neglected, yet important, area. It is shown that the regression calibration approach bias correction methods are useful when the Berkson errors are independent...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Althubaiti, A., Donev, A. Tags: Articles Source Type: research

A minimal net reclassification improvement to assess predictions of intensive care mortality
Conclusion Reclassification methods, particularly the minimal net reclassification improvement, seem to be clinically relevant when used with continuous clinical data with no known threshold. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Redondo, Y. T. L., Lambert, J., Chevret, S. Tags: Articles Source Type: research

A Bayesian path analysis to estimate causal effects of bazedoxifene acetate on incidence of vertebral fractures, either directly or through non-linear changes in bone mass density
Conclusions Computational methods are available to evaluate and interpret the surrogacytic capability of a biomarker of a primary outcome. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Detilleux, J., Reginster, J.-Y., Chines, A., Bruyere, O. Tags: Articles Source Type: research

Analysis of Poisson frequency data under a simple crossover trial
When the frequency of occurrence for an event of interest follows a Poisson distribution, we develop asymptotic and exact procedures for testing non-equality, non-inferiority and equivalence, as well as asymptotic and exact interval estimators for the ratio of mean frequencies between two treatments under a simple crossover design. Using Monte Carlo simulations, we evaluate the performance of these test procedures and interval estimators in a variety of situations. We note that all asymptotic test procedures developed here can generally perform well with respect to Type I error and can be preferable to the exact test proce...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Lui, K.-J., Chang, K.-C. Tags: Articles Source Type: research

Evaluating treatment effect within a multivariate stochastic ordering framework: Nonparametric combination methodology applied to a study on multiple sclerosis
Multiple sclerosis is an autoimmune complex disease that affects the central nervous system. It has a multitude of symptoms that are observed in different people in many different ways. At this time, there is no definite cure for multiple sclerosis. However, therapies that slow the progression of disability, controlling symptoms and helping patients to maintain a normal quality of life, are available. We will focus on relapsing–remitting multiple sclerosis patients treated with interferons or glatiramer acetate. These treatments have been shown to be effective, but their relative effectiveness has not been well estab...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Brombin, C., Di Serio, C. Tags: Articles Source Type: research

Meta-analysis using Dirichlet process
This article develops a Bayesian approach for meta-analysis using the Dirichlet process. The key aspect of the Dirichlet process in meta-analysis is the ability to assess evidence of statistical heterogeneity or variation in the underlying effects across study while relaxing the distributional assumptions. We assume that the study effects are generated from a Dirichlet process. Under a Dirichlet process model, the study effects parameters have support on a discrete space and enable borrowing of information across studies while facilitating clustering among studies. We illustrate the proposed method by applying it to a data...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Muthukumarana, S., Tiwari, R. C. Tags: Articles Source Type: research

Bayesian analysis of a disability model for lung cancer survival
Bayesian reasoning, survival analysis and multi-state models are used to assess survival times for Stage IV non-small-cell lung cancer patients and the evolution of the disease over time. Bayesian estimation is done using minimum informative priors for the Weibull regression survival model, leading to an automatic inferential procedure. Markov chain Monte Carlo methods have been used for approximating posterior distributions and the Bayesian information criterion has been considered for covariate selection. In particular, the posterior distribution of the transition probabilities, resulting from the multi-state model, cons...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Armero, C., Cabras, S., Castellanos, M., Perra, S., Quiros, A., Oruezabal, M., Sanchez-Rubio, J. Tags: Articles Source Type: research

Causal inference with a quantitative exposure
The current statistical literature on causal inference is mostly concerned with binary or categorical exposures, even though exposures of a quantitative nature are frequently encountered in epidemiologic research. In this article, we review the available methods for estimating the dose–response curve for a quantitative exposure, which include ordinary regression based on an outcome regression model, inverse propensity weighting and stratification based on a propensity function model, and an augmented inverse propensity weighting method that is doubly robust with respect to the two models. We note that an outcome regr...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Zhang, Z., Zhou, J., Cao, W., Zhang, J. Tags: Articles Source Type: research

Restricted ROC curves are useful tools to evaluate the performance of tumour markers
In this study, a new statistical approach is proposed to perform this task. Furthermore, a statistical test associated with the area under a ROC curve corresponding to informative values only (restricted ROC curve) is provided and its properties are explored by extensive simulations. Finally, the proposed method is applied to a real data set containing peripheral blood levels of six tumour markers proposed for the diagnosis of neuroblastoma. A new approach to combine couples of markers for classification purposes is also illustrated. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Parodi, S., Muselli, M., Carlini, B., Fontana, V., Haupt, R., Pistoia, V., Corrias, M. Tags: Articles Source Type: research

Methods for meta-analysis of individual participant data from Mendelian randomisation studies with binary outcomes
Mendelian randomisation is an epidemiological method for estimating causal associations from observational data by using genetic variants as instrumental variables. Typically the genetic variants explain only a small proportion of the variation in the risk factor of interest, and so large sample sizes are required, necessitating data from multiple sources. Meta-analysis based on individual patient data requires synthesis of studies which differ in many aspects. A proposed Bayesian framework is able to estimate a causal effect from each study, and combine these using a hierarchical model. The method is illustrated for data ...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Burgess, S., Thompson, S. G., CRP CHD Genetics Collaboration Tags: Articles Source Type: research

Development and evaluation of multi-marker risk scores for clinical prognosis
Heart failure research suggests that multiple biomarkers could be combined with relevant clinical information to more accurately quantify individual risk and guide patient-specific treatment strategies. Therefore, statistical methodology is required to determine multi-marker risk scores that yield improved prognostic performance. Development of a prognostic score that combines biomarkers with clinical variables requires specification of an appropriate statistical model and is most frequently achieved using standard regression methods such as Cox regression. We demonstrate that care is needed in model specification and that...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: French, B., Saha-Chaudhuri, P., Ky, B., Cappola, T. P., Heagerty, P. J. Tags: Articles Source Type: research

Unconditional tests for comparing two ordered multinomials
We consider two exact unconditional procedures to test the difference between two multinomials with ordered categorical data. Exact unconditional procedures are compared to other approaches based on the Wilcoxon mid-rank test and the proportional odds model. We use a real example from an arthritis pain study to illustrate the various test procedures and provide an extensive numerical study to compare procedures with regards to type I error rates and power under the unconditional framework. The exact unconditional procedure based on estimation followed by maximization is generally more powerful than other procedures, and is...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Shan, G., Ma, C. Tags: Articles Source Type: research

Bayesian approach to non-inferiority trials for normal means
Regulatory framework recommends that novel statistical methodology for analyzing trial results parallels the frequentist strategy, e.g. the new method must protect type-I error and arrive at a similar conclusion. Keeping these in mind, we construct a Bayesian approach for non-inferiority trials with normal response. A non-informative prior is assumed for the mean response of the experimental treatment and Jeffrey's prior for its corresponding variance when it is unknown. The posteriors of the mean response and variance of the treatment in historical trials are then assumed as priors for its corresponding parameters in the ...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Gamalo, M. A., Wu, R., Tiwari, R. C. Tags: Articles Source Type: research

Longitudinal data analysis with non-ignorable missing data
A common problem in the longitudinal data analysis is the missing data problem. Two types of missing patterns are generally considered in statistical literature: monotone and non-monotone missing data. Nonmonotone missing data occur when study participants intermittently miss scheduled visits, while monotone missing data can be from discontinued participation, loss to follow-up, and mortality. Although many novel statistical approaches have been developed to handle missing data in recent years, few methods are available to provide inferences to handle both types of missing data simultaneously. In this article, a latent ran...
Source: Statistical Methods in Medical Research - February 16, 2016 Category: Statistics Authors: Tseng, C.-h., Elashoff, R., Li, N., Li, G. Tags: Articles Source Type: research