Volume 53 (2016): Issue 2 (December 2016)

The continual reassessment method is a model-based procedure, described in the literature, used to determine the maximum tolerated dose in phase I clinical trials. The maximum tolerated dose can also be found under the framework of D-optimum design, where information is gathered in such a way so that asymptotic variability in the parameter estimates in minimised. This paper investigates the two methods under some realistic settings to explore any potential differences between them. Simulation studies for six plausible dose-response scenarios show that D-optimum design can work well in comparison with the continual reassessment method in many cases. The D-optimum design is also found to allocate doses from the extremes of the design region to the patients in a trial.

Methods for dealing with missing data in clinical trials have received increased attention from the regulators and practitioners in the pharmaceutical industry over the last few years. Consideration of missing data in a study is important as they can lead to substantial biases and have an impact on overall statistical power. This problem may be caused by patients dropping before completion of the study. The new guidelines of the International Conference on Harmonization place great emphasis on the importance of carefully choosing primary analysis methods based on clearly formulated assumptions regarding the missingness mechanism. The reason for dropout or withdrawal would be either related to the trial (e.g. adverse event, death, unpleasant study procedures, lack of improvement) or unrelated to the trial (e.g. moving away, unrelated disease). We applied selection models on liver cirrhosis patient data to analyse the treatment efficiency comparing the surgery of liver cirrhosis patients with consenting for participation HFLPC (Human Fatal Liver Progenitor Cells) infusion with surgery alone. It was found that comparison between treatment conditions when missing values are ignored potentially leads to biased conclusions.

We consider an incomplete split-plot design (ISPD) with two factors generated by the semi-Kronecker product of two α-resolvable designs. We use an α-resolvable design for the whole plot treatments and an affine α-resolvable design for the subplot treatments. We characterize the ISPDs with respect to the general balance property, and we give the stratum efficiency factors for the ISPDs.

This paper considers main effects plans used to study m two-level factors using n runs which are partitioned into b blocks of equal size k = n/b. The assumptions are adopted that n ≡ 2 (mod 8) and k > 2 is even. Certain designs not having all main effects orthogonal to blocks were shown by Jacroux (2011a) to be D-optimal when (m − 2)(k − 2) + 2 ⩽ n ⩽ (m − 1)(k − 2) + 2. Here, we extend that result. For (m − 3)(k − 2) + 2 ⩽ n < (m − 2)(k − 2) + 2, the D-optimality of those designs is proved. Moreover, their D-efficiency is shown to be close to one for 2(m + 1) ⩽ n < (m − 3)(k − 2) + 2, indicating their good performance under the criterion of D-optimality.

Recycling of crop residues is essential to sustain soil fertility and crop production. Despite the positive effect of straw incorporation, the slow decomposition of that organic substance is a serious issue. The aim of the study was to assess the influence of winter wheat straws with different degrees of stem solidness on the rate of decomposition and soil properties. An incubation experiment lasting 425 days was carried out in controlled conditions. To perform analyses, soil samples were collected after 7, 14, 21, 28, 35, 49, 63, 77, 91, 119, 147, 175, 203, 231, 259, 313, 341, 369, 397 and 425 days of incubation. The addition of two types of winter wheat straw with different degree of stem solidness into the sandy soil differentiated the experimental treatments. The results demonstrate that straw mineralization was a relatively slow process and did not depend on the degree of filling of the stem by pith. Multivariate functional principal component analysis (MFPC) gave proof of significant variation between the control soil and the soil incubated with the straws. The first functional principal component describes 48.53% and the second 18.55%, of the variability of soil properties. Organic carbon, mineral nitrogen and sum of bases impact on the first functional principal component, whereas, magnesium, sum of bases and total nitrogen impact on the second functional principal component.

In breeding experiments conducted prior to tests connected with the registration of new breeding lines of crops, pre-preliminary and preliminary trials are carried out. In this study a comparison was made among some models of analysis of variance, in relation to the selection of new breeding lines of spring barley (Hordeum vulgare L.). The aim is to determine whether the choice of model of analysis of variance may influence the choice of tested breeding lines. The trait considered was the yield in two years of trials. A more comprehensive analysis of variance model was found to be superior. It was also found that the results of analyses performed using average measurements for lines significantly differ from those obtained on the basis of all measurements. It was concluded that the type of ANOVA model used may have an impact on inferences about breeding lines. Moreover, a lack of stability in the yields of tested lines was revealed, implying the necessity of several years of trials.

This paper concerns methods of choosing appropriate models for longitudinal studies. Attention is paid to three criteria: the marginal Akaike Information Criterion (mAIC), the conditional Akaike Information Criterion (cAIC), and the corrected conditional Akaike Information Criterion (ccAIC). We consider these criteria based on an example concerning the effect of storage time and addition of flaxseed (Linum usitatissimum L.) preparations (i.e. ground flaxseeds, defatted flaxseed meal and flaxseed ethanolic extract) on changes in lipid oxidation and fatty acid composition during the storage of liver pâté with partial substitution of fat with flax oil.