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Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Gomez-Rubio, V. Tags: Book reviews Source Type: research

Misclassification of outcome in case-control studies: Methods for sensitivity analysis
Case–control studies are potentially open to misclassification of disease outcome which may be unrelated to risk factor exposure (non-differential), thus underestimating associations, or related to risk factor exposure (differential), thus causing more serious bias. We conducted a systematic literature review for methods of adjusting for outcome misclassification in case–control studies. We also applied methods to simulated data with known outcome misclassification to assess performance of these methods. Finally, real data from the Prostate Testing for Cancer and Treatment (ProtecT) randomised controlled trial ...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Gilbert, R., Martin, R. M., Donovan, J., Lane, J. A., Hamdy, F., Neal, D. E., Metcalfe, C. Tags: Articles Source Type: research

Confidence intervals for intraclass correlation coefficients in variance components models
Confidence intervals for intraclass correlation coefficients in agreement studies with continuous outcomes are model-specific and no generic approach exists. This paper provides two generic approaches for intraclass correlation coefficients of the form q=1Qq2/(q=1Qq2+p=Q+1Pp2). The first approach uses Satterthwaite’s approximation and an F-distribution. The second approach uses the first and second moments of the intraclass correlation coefficient estimate in combination with a Beta distribution. Both approaches are based on the restricted maximum likelihood estimates for the variance components involved. Simulation ...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Demetrashvili, N., Wit, E. C., van den Heuvel, E. R. Tags: Articles Source Type: research

Bayesian analysis of transformation latent variable models with multivariate censored data
Transformation latent variable models are proposed in this study to analyze multivariate censored data. The proposed models generalize conventional linear transformation models to semiparametric transformation models that accommodate latent variables. The characteristics of the latent variables were assessed based on several correlated observed indicators through measurement equations. A Bayesian approach was developed with Bayesian P-splines technique and the Markov chain Monte Carlo algorithm to estimate the unknown parameters and transformation functions. Simulation shows that the performance of the proposed methodology...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Song, X.-Y., Pan, D., Liu, P.-F., Cai, J.-H. Tags: Articles Source Type: research

Evaluating treatment effectiveness under model misspecification: A comparison of targeted maximum likelihood estimation with bias-corrected matching
Statistical approaches for estimating treatment effectiveness commonly model the endpoint, or the propensity score, using parametric regressions such as generalised linear models. Misspecification of these models can lead to biased parameter estimates. We compare two approaches that combine the propensity score and the endpoint regression, and can make weaker modelling assumptions, by using machine learning approaches to estimate the regression function and the propensity score. Targeted maximum likelihood estimation is a double-robust method designed to reduce bias in the estimate of the parameter of interest. Bias-correc...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Kreif, N., Gruber, S., Radice, R., Grieve, R., Sekhon, J. S. Tags: Articles Source Type: research

Can we believe the DAGs? A comment on the relationship between causal DAGs and mechanisms
Directed acyclic graphs (DAGs) play a large role in the modern approach to causal inference. DAGs describe the relationship between measurements taken at various discrete times including the effect of interventions. The causal mechanisms, on the other hand, would naturally be assumed to be a continuous process operating over time in a cause–effect fashion. How does such immediate causation, that is causation occurring over very short time intervals, relate to DAGs constructed from discrete observations? We introduce a time-continuous model and simulate discrete observations in order to judge the relationship between ...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Aalen, O., Roysland, K., Gran, J., Kouyos, R., Lange, T. Tags: Articles Source Type: research

Graphical model-based O/E control chart for monitoring multiple outcomes from a multi-stage healthcare procedure
Most statistical process control programmes in healthcare focus on surveillance of outcomes at the final stage of a procedure, such as mortality or failure rates. Such an approach ignores the multi-stage nature of these procedures, in which a patient progresses through several stages prior to the final stage. In this paper, we introduce a novel approach to statistical process control programmes in healthcare. Our proposed approach is based on the regression adjustment and multi-stage control charts that have been in use in industrial applications for decades. Three advantages of the approach are: better understanding of ho...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Sibanda, N. Tags: Articles Source Type: research

Confidence intervals for proportion difference from two independent partially validated series
Partially validated series are common when a gold-standard test is too expensive to be applied to all subjects, and hence a fallible device is used accordingly to measure the presence of a characteristic of interest. In this article, confidence interval construction for proportion difference between two independent partially validated series is studied. Ten confidence intervals based on the method of variance estimates recovery (MOVER) are proposed, with each using the confidence limits for the two independent binomial proportions obtained by the asymptotic, Logit-transformation, Agresti–Coull and Bayesian methods. T...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Qiu, S.-F., Poon, W.-Y., Tang, M.-L. Tags: Articles Source Type: research

Comparison of treatments in a cataract surgery with circular response
Circular data are a natural outcome in many biomedical studies, e.g. some measurements in ophthalmologic studies, degrees of rotation of hand or waist, etc. With reference to a real data set on astigmatism induced in two types of cataract surgeries we carry out some two-sample testing problems with the possibility of common or different concentration parameters in the circular set up. Detailed simulation study and the analysis of the data set, including redesigning the cataract surgery data, are carried out. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Biswas, A., Dutta, S., Laha, A. K., Bakshi, P. K. Tags: Articles Source Type: research

The performance of different propensity score methods for estimating absolute effects of treatments on survival outcomes: A simulation study
We describe how three different propensity score methods, propensity score matching, stratification on the propensity score and inverse probability of treatment weighting using the propensity score, can be used to estimate absolute measures of treatment effect on survival outcomes. These methods are all based on estimating marginal survival functions under treatment and lack of treatment. We then conducted an extensive series of Monte Carlo simulations to compare the relative performance of these methods for estimating the absolute effects of treatment on survival outcomes. We found that stratification on the propensity sc...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Austin, P. C., Schuster, T. Tags: Articles Source Type: research

Level of evidence for promising subgroup findings in an overall non-significant trial
In drug development and drug licensing, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population, but there appears to be benefit in a relevant, pre-defined subgroup. This raises the question, how strong the evidence from such a subgroup is, and which confirmatory testing strategies are the most appropriate ones. Hence, we considered the type I error and the power of a subgroup result in a trial with non-significant overall results and of suitable replication strategies. In the case of a single trial, the inflation of the overall type I error is substantial and can be up to twice...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Tanniou, J., Tweel, I. v. d., Teerenstra, S., Roes, K. C. Tags: Articles Source Type: research

A Bayesian model for joint analysis of multivariate repeated measures and time to event data in crossover trials
Joint modeling of longitudinal and survival data has become a popular technique in analyzing longitudinal clinical trials. In this discussion, the potentials of joint modeling are explored for analyzing time to event and multivariate repeated measures in crossover studies. The work is motivated by a real-life crossover study with three visual analog scale responses and a time to event response. To recover the information lost due to censoring of the time to event variable, we propose a Bayesian joint model to analyze the visual analog scale and time to event responses jointly, leveraging the moderate associations among the...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Liu, F., Li, Q. Tags: Articles Source Type: research

Notes on testing equality and interval estimation in Poisson frequency data under a three-treatment three-period crossover trial
When the frequency of event occurrences follows a Poisson distribution, we develop procedures for testing equality of treatments and interval estimators for the ratio of mean frequencies between treatments under a three-treatment three-period crossover design. Using Monte Carlo simulations, we evaluate the performance of these test procedures and interval estimators in various situations. We note that all test procedures developed here can perform well with respect to Type I error even when the number of patients per group is moderate. We further note that the two weighted-least-squares (WLS) test procedures derived here a...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Lui, K.-J., Chang, K.-C. Tags: Articles Source Type: research

Spatial generalised linear mixed models based on distances
We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, w...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Melo, O. O., Mateu, J., Melo, C. E. Tags: Articles Source Type: research

Jackknife empirical likelihood confidence regions for the evaluation of continuous-scale diagnostic tests with verification bias
Recently, Wang and Qin proposed various bias-corrected empirical likelihood confidence regions for any two of the three parameters, sensitivity, specificity, and cut-off value, with the remaining parameter fixed at a given value in the evaluation of a continuous-scale diagnostic test with verification bias. In order to apply those methods, quantiles of the limiting weighted chi-squared distributions of the empirical log-likelihood ratio statistics should be estimated. In order to facilitate application and reduce computation burden, in this paper, jackknife empirical likelihood-based methods are proposed for any pairs of s...
Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Wang, B., Qin, G. Tags: Articles Source Type: research