Testing for lack of fit in blocked and split-plot response surface designs

Textbooks on response surface methodology emphasize the importance of lack-of-fit tests when fitting response surface models, and stress that, to be able to test for lack of fit, designed experiments should have replication and allow for pure-error estimation. In this paper, we show how to obtain pure-error estimates and how to carry out a lack-of-fit test when the experiment is not completely randomized, but a blocked experiment, a split-plot experiment, or any other multi-stratum experiment. Our approach to calculating pure-error estimates is based on residual maximum likelihood (REML) estimation of the variance components in a full treatment model. It generalizes the one suggested by Vining et al. (2005) in the sense that it works for a broader set of designs and for replicates other than center point replicates. Our lack-of-fit test also generalizes the test proposed by Khuri (1992) for data from blocked experiments because it exploits replicates other than center point replicates and works for split-plot and other multi-stratum designs as well. We provide analytical expressions for the test statistic and the corresponding degrees of freedom, and demonstrate how to perform the lack-of-fit test in the SAS procedure MIXED. We re-analyze several published data sets and discover a few instances in which the usual response surface model exhibits significant lack of fit

BLOCKING FACTORIAL DESIGNS IN GREENHOUSE EXPERIMENTS

Experiments in greenhouses usually have to be conducted with very limited resources. This makes it particularly important to control the between plot variation by appropriate use of blocking. Many greenhouse experiments are naturally laid out in a pattern that makes a class of designs known as semi-Latin squares useful. Their properties have been studied recently by a number of authors and this work is reviewed. Often, the experimental treatments will have a factorial structure. An example of a 23 structure is used to show how factorial treatments can be assigned to treatment labels to ensure that the appropriate information is obtained from the experiment

Factorial and response surface designs robust to missing observations

Made available in DSpace on 2018-11-26T17:35:05Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-09-01Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Compound optimum design criteria which allow pure error degrees of freedom may produce designs that break down when even a single run is missing, if the number of experimental units is small. The inclusion, in the compound criteria, of a measure of leverage uniformity is proposed in order to produce designs that are more robust to missing observations. By appropriately choosing the weights of each part of the criterion, robust designs are obtained that are also highly efficient in terms of other properties. Applications to various experimental setups show the advantages of the new methods. (C) 2016 Elsevier B.V. All rights reserved.USP UFSCar, Programa Interinst Posgrad Estat, Sao Carlos, SP, BrazilKings Coll London, Dept Math, London, EnglandUniv Estadual Paulista, Dept Bioestat, IB, Botucatu, SP, BrazilUniv Estadual Paulista, Dept Bioestat, IB, Botucatu, SP, BrazilFAPESP: 2014/01818-

The targeted histone deacetylase inhibitor tefinostat (CHR-2845) shows selective in vitro efficacy in monocytoid-lineage leukaemias

Tefinostat (CHR-2845) is a novel monocyte/macrophage-targeted histone deacetylase (HDAC) inhibitor which is cleaved into its active acid by the intracellular esterase human carboxylesterase-1 (hCE-1). The in vitro efficacy of tefinostat was characterised in cell lines and in a cohort of 73 primary AML and CMML samples. Dose-dependent induction of apoptosis and significant growth inhibitory effects were seen in myelomonocytic (M4), monocytic/monoblastic (M5) and CMML samples in comparison to non-monocytoid AML sub-types (p = 0.007). Importantly, no growth inhibitory effects were seen in normal bone marrow CD34+ cells exposed to AML-toxic doses of tefinostat in clonogenic assays. Expression of hCE-1 was measured by intracellular flow cytometry and immunoblotting across the cohort, with highest levels seen in M5 AML patients. hCE-1 levels correlated with significantly increased tefinostat sensitivity (low EC50) as measured by growth inhibition assays (p = 0.001)and concomitant elevation of the mature monocytoid marker CD14+. Strong induction of intracellular histone protein acetylation was observed in tefinostat-responsive samples, as were high levels of the DNA damage sensor γ-H2A.X, highlighting potential biomarkers of patient responsiveness. Synergistic interaction between tefinostat and the current standard treatment cytarabine was demonstrated in dose response and clonogenic assays using simultaneous drug addition in primary samples (median Combination Index value = 0.51). These data provide a strong rationale for the further clinical evaluation of tefinostat in monocytoid-lineage haematological neoplasms including CMML and monocyte-lineage AMLs

Professor Gopal Kanji\u27s Retirement as Editor of Journal of Applied Statistics

(First paragraph) This. issue of Journal of Applied Statistics marks the first in its history which does not fall under the editorship of its founder Professor Gopal Kanji. Following his retirement from the role we would like to use this editorial to outline the history and development of the Journal and pay tribute to the many achievements of Gopal’s career

Changing trends in β-hemolytic streptococcal bacteremia in Manitoba, Canada:2007-2012

OBJECTIVES: European surveillance studies have reported an increasing incidence of β-hemolytic group G streptococcal bacteremia, but no studies have evaluated trends in β-hemolytic streptococcal bacteremia in North America. METHODS: We reviewed bacteremic episodes and positive throat swab cultures from two tertiary care centers in Manitoba, Canada, from January 2007 to December 2012. RESULTS: During the study period, 19 864 bacteremic episodes, and 9948 positive throat swabs were identified. There were 1025 (5.16%) bacteremic episodes attributable to β-hemolytic streptococci: 425 (2.03%), 339 (1.71%), 62 (0.31%), and 199 (0.95%) to β-hemolytic groups A, B, C, and G streptococci, respectively. From 2007 to 2012, there were significant increases in the proportion of bacteremia attributable to β-hemolytic streptococci in general (6.32% vs. 4.02%; p<0.0001; linear trend test, p<0.0001), and to groups G (1.49% vs. 0.43%; p<0.0001; linear trend test, p<0.0001) and C (0.58% vs. 0.13%; p=0.0068; linear trend test, p=0.0105) β-hemolytic streptococci in particular. Bacteremia attributable to groups A and B β-hemolytic streptococci and Streptococcus pneumoniae were unchanged. There were no changes in the distribution of β-hemolytic streptococcal groups among throat swabs. CONCLUSIONS: Bacteremia attributable to β-hemolytic groups G and C streptococci increased in Manitoba, Canada. Further study of the factors underlying these changes is required