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BACKGROUND Smoking cessation programmes delivered via mobile phone text messaging show increases in self-reported quitting in the short term. We assessed the effect of an automated smoking cessation programme delivered via mobile phone text messaging on continuous abstinence, which was biochemically verified at 6 months. METHODS In this single-blind,(More)
The use of repeated measures of an outcome variable to improve statistical power and precision in randomized clinical trials and cohort studies is well documented. Linear mixed models have great utility in the analysis of such studies in many medical applications including imaging. However, in imaging studies and other applications the basic outcome can be(More)
Missing covariate data commonly occur in epidemiological and clinical research, and are often dealt with using multiple imputation. Imputation of partially observed covariates is complicated if the substantive model is non-linear (e.g. Cox proportional hazards model), or contains non-linear (e.g. squared) or interaction terms, and standard software(More)
Part of the recent literature on the evaluation of biomarkers as surrogate endpoints starts from a multitrial context, which leads to a definition of validity in terms of the quality of both trial-level and individual-level association between the surrogate and true endpoints (Buyse et al., 2000, Biostatistics1, 49-67). These authors concentrated on(More)
Salient sensory experiences often have a strong emotional tone, but the neuropsychological relations between perceptual characteristics of sensory objects and the affective information they convey remain poorly defined. Here we addressed the relationship between sound identity and emotional information using music. In two experiments, we investigated(More)
1. Analysis for the renal-cell carcinoma trial example We analysed four sets of data. First, the data as shown in Figure 1 in the paper were analysed. There was 64% dropout for the control arm and 70% for the experimental arm. To illustrate a variety of dropout scenarios, a complete dataset was created using multiple imputation (see glossary and below), and(More)
It is our experience that in many settings, crossover trials that have within-period baseline measurements are analyzed wrongly. A "conventional" analysis of covariance in this setting uses each baseline as a covariate for the following outcome variable in the same period but not for any other outcome. If used with random subject effects such an analysis(More)
Protocol deviations, for example, due to early withdrawal and noncompliance, are unavoidable in clinical trials. Such deviations often result in missing data. Additional assumptions are then needed for the analysis, and these cannot be definitively verified from the data at hand. Thus, as recognized by recent regulatory guidelines and reports, clarity about(More)