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.

The covariate-adjusted frequency plot
Count data arise in numerous fields of interest. Analysis of these data frequently require distributional assumptions. Although the graphical display of a fitted model is straightforward in the univariate scenario, this becomes more complex if covariate information needs to be included into the model. Stratification is one way to proceed, but has its limitations if the covariate has many levels or the number of covariates is large. The article suggests a marginal method which works even in the case that all possible covariate combinations are different (i.e. no covariate combination occurs more than once). For each covaria...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Holling, H., Böhning, W., Böhning, D., Formann, A. K. Tags: Articles Source Type: research

Estimating efficacy in the presence of non-ignorable non-trial interventions in the Helsinki Psychotherapy Study
In a randomised clinical trial with a longitudinal outcome, analyses of the efficacy of the study treatments may be complicated by both non-trial interventions, which have not been administered by the researcher, and sparsely measured outcome values. The delay between the change in outcome and the starting of the non-trial intervention may be much shorter than the time intervals between the actual measurements. We propose a model that accounts for the possible dynamic interdependence between the longitudinal outcome and time-to-event data. The model is based on discretising time into short intervals. This results in a miss...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Härkänen, T., Arjas, E., Laaksonen, M. A., Lindfors, O., Haukka, J., Knekt, P. Tags: Articles Source Type: research

Development of a pediatric body mass index using longitudinal single-index models
In this study, we propose an alternative pediatric body mass measure for prediction of blood pressure based on recorded height and weight data using single-index modeling techniques. Specifically, we present a general form of partially linear single-index mixed effect models for the determination of this new metric. A methodological contribution of this research is the development of an efficient algorithm for the fitting of a general class of partially linear single-index models in longitudinal data situations. The proposed model and related model fitting algorithm are easily implementable in most computational platforms....
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Wu, J., Tu, W. Tags: Articles Source Type: research

Meta-analysis of two-arm studies: Modeling the intervention effect from survival probabilities
Pooling the hazard ratios is not always feasible in meta-analyses of two-arm survival studies, because the measure of the intervention effect is not systematically reported. An alternative approach proposed by Moodie et al. is to use the survival probabilities of the included studies, all collected at a single point in time: the intervention effect is then summarised as the pooled ratio of the logarithm of survival probabilities (which is an estimator of the hazard ratios when hazards are proportional). In this article, we propose a generalization of this method. By using survival probabilities at several points in time, t...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Combescure, C., Courvoisier, D., Haller, G., Perneger, T. Tags: Articles Source Type: research

A cure rate survival model under a hybrid latent activation scheme
In lifetimes studies, the occurrence of an event (such as tumor detection or death) might be caused by one of many competing causes. Moreover, both the number of causes and the time-to-event associated with each cause are not usually observable. The number of causes can be zero, corresponding to a cure fraction. In this article, we propose a method of estimating the numerical characteristics of unobservable stages (such as initiation, promotion and progression) of carcinogenesis from data on tumor size at detection in the presence of latent competing causes. To this end, a general survival model for spontaneous carcinogene...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Borges, P., Rodrigues, J., Louzada, F., Balakrishnan, N. Tags: Articles Source Type: research

Bayesian multiple imputation for missing multivariate longitudinal data from a Parkinson's disease clinical trial
In Parkinson's disease (PD) clinical trials, Parkinson's disease is studied using multiple outcomes of various types (e.g. binary, ordinal, continuous) collected repeatedly over time. The overall treatment effects across all outcomes can be evaluated based on a global test statistic. However, missing data occur in outcomes for many reasons, e.g. dropout, death, etc., and need to be imputed in order to conduct an intent-to-treat analysis. We propose a Bayesian method based on item response theory to perform multiple imputation while accounting for multiple sources of correlation. Sensitivity analysis is performed under vari...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Luo, S., Lawson, A. B., He, B., Elm, J. J., Tilley, B. C. Tags: Articles Source Type: research

Near efficient target allocations in response-adaptive randomization
Traditionally optimal target allocation proportions for response-adaptive designs are derived by completely ignoring the actual adaptive randomization procedure. Considering efficiency of the allocation designs, we derive near efficient target proportions to balance between individual and collective ethics. Performance of the derived allocation targets are assessed numerically for binary, normal and exponential responses. Generalization for multiple treatments is also addressed. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Biswas, A., Bhattacharya, R. Tags: Articles Source Type: research

A Bayesian normal mixture accelerated failure time spatial model and its application to prostate cancer
In the United States, prostate cancer is the third most common cause of death from cancer in males of all ages, and the most common cause of death from cancer in males over age 75. It has been recognized that the incidence of the prostate cancer is high in African Americans, and its occurrence and progression may be impacted by geographical factors. In order to investigate the spatial effects and racial disparities for prostate cancer in Louisiana, in this article we propose a normal mixture accelerated failure time spatial model, which does not require the proportional hazards assumption and allows the multi-model distrib...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Wang, S., Zhang, J., Lawson, A. B. Tags: Articles Source Type: research

Maximum likelihood estimation of time to first event in the presence of data gaps and multiple events
We propose a novel likelihood method for analyzing time-to-event data when multiple events and multiple missing data intervals are possible prior to the first observed event for a given subject. This research is motivated by data obtained from a heart monitor used to track the recovery process of subjects experiencing an acute myocardial infarction. The time to first recovery, T1, is defined as the time when the ST-segment deviation first falls below 50% of the previous peak level. Estimation of T1 is complicated by data gaps during monitoring and the possibility that subjects can experience more than one recovery. If gaps...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Green, C. L., Brownie, C., Boos, D. D., Lu, J.-C., Krucoff, M. W. Tags: Articles Source Type: research

A comparison of incomplete-data methods for categorical data
We studied four methods for handling incomplete categorical data in statistical modeling: (1) maximum likelihood estimation of the statistical model with incomplete data, (2) multiple imputation using a loglinear model, (3) multiple imputation using a latent class model, (4) and multivariate imputation by chained equations. Each method has advantages and disadvantages, and it is unknown which method should be recommended to practitioners. We reviewed the merits of each method and investigated their effect on the bias and stability of parameter estimates and bias of the standard errors. We found that multiple imputation usi...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: van der Palm, D. W., van der Ark, L. A., Vermunt, J. K. Tags: Articles Source Type: research

Analysing cognitive test data: Distributions and non-parametric random effects
This article explores alternative distributions for the outcome variable in mixed models fitted to mini mental state examination scores from a longitudinal study of ageing. Model fit improved when a beta-binomial distribution was chosen as the distribution for the response variable. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Muniz-Terrera, G., Hout, A. v. d., Rigby, R., Stasinopoulos, D. Tags: Articles Source Type: research

Estimation of sensitivity depending on sojourn time and time spent in preclinical state
The probability model for periodic screening was extended to provide statistical inference for sensitivity depending on sojourn time, in which the sensitivity was modeled as a function of time spent in the preclinical state and the sojourn time. The likelihood function with the proposed sensitivity model was then evaluated with simulated data to check its reliability in terms of the mean estimation and the standard error. Simulation results showed that the maximum likelihood estimates of the proposed model have little bias and small standard errors. The extended probability model was further applied to the Johns Hopkins Lu...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Kim, S., Wu, D. Tags: Articles Source Type: research

Some recommendations for multi-arm multi-stage trials
Multi-arm multi-stage designs can improve the efficiency of the drug-development process by evaluating multiple experimental arms against a common control within one trial. This reduces the number of patients required compared to a series of trials testing each experimental arm separately against control. By allowing for multiple stages experimental treatments can be eliminated early from the study if they are unlikely to be significantly better than control. Using the TAILoR trial as a motivating example, we explore a broad range of statistical issues related to multi-arm multi-stage trials including a comparison of diffe...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Wason, J., Magirr, D., Law, M., Jaki, T. Tags: Articles Source Type: research

Comparison of four methods for deriving hospital standardised mortality ratios from a single hierarchical logistic regression model
There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data – patients nested within hospitals – and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocat...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Mohammed, M. A., Manktelow, B. N., Hofer, T. P. Tags: Articles Source Type: research

Power and sample size calculations for evaluating mediation effects in longitudinal studies
Current methods of power and sample size calculations for the design of longitudinal studies to evaluate mediation effects are mostly based on simulation studies and do not provide closed-form formulae. A further challenge due to the longitudinal study design is the consideration of missing data, which almost always occur in longitudinal studies due to staggered entry or drop out. In this article, we consider the product of coefficients as a measure for the longitudinal mediation effect and evaluate three methods for testing the hypothesis on the longitudinal mediation effect: the joint significant test, the normal approxi...
Source: Statistical Methods in Medical Research - April 21, 2016 Category: Statistics Authors: Wang, C., Xue, X. Tags: Articles Source Type: research