Author(s):  
Margarita Echeverri ◽  
David Anderson ◽  
Anna Nápoles ◽  
Jacqueline Haas ◽  
Marc Johnson ◽  
...  

Although it has been well documented that poor health literacy is associated with limited participation in cancer clinical trials, studies assessing the relationships between cancer health literacy (CHL) and participation in research among diverse populations are lacking. In this study, we examined the relationship between CHL and willingness to participate in cancer research and/or donate bio-specimens (WPRDB) among African Americans, Latinos, and Whites. Participants completed the Cancer Health Literacy Test and the Multidimensional Cancer Literacy Questionnaire. Total-scale and subscale scores, frequencies, means, and distributions were computed. Analyses of variance, the Bonferroni procedure, and the Holm method were used to examine significant differences among groups. Cronbach’s alphas estimated scales’ internal consistency reliability. Significant interactions were found between race/ethnicity, gender, and CHL on WPRDB scales and subscale scores, even after education and age were taken into account. Our study confirms that CHL plays an important role that should be considered and researched further. The majority of participants were more willing to participate in non-invasive research studies (surveys, interviews, and training) or collection of bio-specimens (saliva, check cells, urine, and blood) and in studies led by their own healthcare providers, and local hospitals and universities. However, participants were less willing to participate in more-invasive studies requiring them to take medications, undergo medical procedures or donate skin/tissues. We conclude that addressing low levels of CHL and using community-based participatory approaches to address the lack of knowledge and trust about cancer research among diverse populations may increase not only their willingness to participate in research and donate bio-specimens, but may also have a positive effect on actual participation rates.


1994 ◽  
Vol 24 (8) ◽  
pp. 1726-1733 ◽  
Author(s):  
J. Beaulieu ◽  
J.-P. Simon

The level of genetic diversity of natural populations of eastern white pine (Pinusstrobus L.) from Quebec was estimated from allozyme variants of 18 loci coding 12 enzyme systems. On average, a white pine population was polymorphic at 50.6% of loci, had 1.96 alleles and 1.22 effective alleles per locus, and observed and expected heterozygosities of 0.176 and 0.180, respectively. The level of genetic diversity was lower in the populations of the St. Lawrence lowlands than in those of western Quebec. This observation will help in guiding the selection program of the eastern white pine improvement program under way in Quebec. Genetic differentiation among sampled populations was weak and accounted for only 2% of the total diversity. The estimate of gene flow was very high, resulting in low values for genetic distances among populations. Only one locus showed a heterogeneity of allelic frequencies among populations after the Bonferroni procedure was applied for simultaneous statistical tests. A cluster analysis based on genetic distances among populations revealed that the Anticosti and Abitibi populations, located at the limit of the natural range of white pine, were similar to populations from regions that were geographically the most distant.


1993 ◽  
Vol 19 (3) ◽  
pp. 707-724 ◽  
Author(s):  
Maria B. Castaiieda ◽  
Joel R. Levin ◽  
Randall B. Dunham

This article describes the Bonferroni multiple-comparison procedure, and makes a case for researchers’ more frequent and appropriate use of it. The procedure is discussed as a test that facilitates investigation of precise and powerful a priori multiple comparisons. Characteristics of the Bonferroni procedure are described in relation to the more familiar Scheffe post hoc multiple-comparison method, and a step-by-step guide for comparing and choosing between the two is provided. The Bonferroni procedure is discussed in detail in the context of one-factor analysis-of-variance designs. Application of the technique is then considered in the context of factorial designs, analyses of covariance, univariate repeated-measures analyses, multivariate analyses of variance, and recent sequential hypothesis-testing extensions. To aid the presentation, an example from the field of management is included.


1988 ◽  
Vol 13 (3) ◽  
pp. 215-226 ◽  
Author(s):  
H. J. Keselman ◽  
Joanne C. Keselman

Two Tukey multiple comparison procedures as well as a Bonferroni and multivariate approach were compared for their rates of Type I error and any-pairs power when multisample sphericity was not satisfied and the design was unbalanced. Pairwise comparisons of unweighted and weighted repeated measures means were computed. Results indicated that heterogenous covariance matrices in combination with unequal group sizes resulted in substantially inflated rates of Type I error for all MCPs involving comparisons of unweighted means. For tests of weighted means, both the Bonferroni and a multivariate critical value limited the number of Type I errors; however, the Bonferroni procedure provided a more powerful test, particularly when the number of repeated measures treatment levels was large.


Author(s):  
Fabio Caraffini

The Stochastic Optimisation Software (SOS) is a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms. It reduces the burden of coding miscellaneous methods for dealing with several bothersome and time-demanding tasks such as parameter tuning, implementation of comparison algorithms and testbed problems, collecting and processing data to display results, measuring algorithmic overhead, etc. SOS provides numerous off-the-shelf methods including 1) customised implementations of statistical tests, such as the Wilcoxon Rank-Sum test and the Holm-Bonferroni procedure, for comparing performances of optimisation algorithms and automatically generate result tables in PDF and LaTeX formats; 2) the implementation of an original advanced statistical routine for accurately comparing couples of stochastic optimisation algorithms; 3) the implementation of a novel testbed suite for continuous optimisation, derived from the IEEE CEC 2014 benchmark, allowing for controlled activation of the rotation operator. each testbed function. Moreover, this article comments on the current state of the literature in stochastic optimisation and highlights similarities shared by modern metaheuristics inspired by nature. It is argued that the vast majority of these algorithms are simply a reformulation of the same methods and that metaheuristics for optimisation should be simply treated as stochastic processes with less emphasis on the inspiring metaphor behind them.


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