The influence of background and demographic factors on the leadership of further education principals

This study is an investigation into the backgrounds of senior managers and leaders in the Further Education (FE) sector in England. In particular, the research aims to establish whether there is a link between the educational, professional or experiential background of a leader and the style of leadership that they perceive they display. There is a paucity of research that has been carried out on the subject of leadership in the further education arena. This thesis focuses on three approaches to leadership, transformational, distributed and managerial, which, it is argued, are the most relevant in the FE sector. The thesis also seeks to explore other factors that have an influence on the way in which FE principals lead. The research is carried out using a mixed method approach. An internet survey and semi-structured interviews are used as the data gathering tools. The study suggests that there are many influences on the way in which FE principals lead which include their background in addition to college culture and the context in which the college operates

A gene-model-free method for linkage analysis of a disease-related-trait based on analysis of proband/sibling pairs

In this paper we investigate the power of finding linkage to a disease locus through analysis of the disease-related traits. We propose two family-based gene-model-free linkage statistics. Both involve considering the distribution of the number of alleles identical by descent with the proband and comparing siblings with the disease-related trait to those without the disease-related-trait. The objective is to find linkages to disease-related traits that are pleiotropic for both the disease and the disease-related-traits. The power of these statistics is investigated for Kofendrerd Personality Disorder-related traits a (Joining/founding cults) and trait b (Fear/discomfort with strangers) of the simulated data. The answers were known prior to the execution of the reported analyses. We find that both tests have very high power when applied to the samples created by combining the data of the three cities for which we have nuclear family data

UO2 CORROSION IN HIGH SURFACE-AREA-TO-VOLUME BATCH EXPERIMENTS

Unsaturated drip tests have been used to investigate the alteration of unirradiated UO{sub 2} and spent UO{sub 2} fuel in an unsaturated environment, such as may be expected in the proposed repository at Yucca Mountain. In these tests, simulated groundwater is periodically injected onto a sample at 90 C in a steel vessel. The solids react with the dripping groundwater and water condensed on surfaces to form a suite of U(VI) alteration phases. Solution chemistry is determined from leachate at the bottom of each vessel after the leachate stops interacting with the solids. A more detailed knowledge of the compositional evolution of the leachate is desirable. By providing just enough water to maintain a thin film of water on a small quantity of fuel in batch experiments, we can more closely monitor the compositional changes to the water as it reacts to form alteration phases

Incorporation of genetic model parameters for cost-effective designs of genetic association studies using DNA pooling

<p>Abstract</p> <p>Background</p> <p>Studies of association methods using DNA pooling of single nucleotide polymorphisms (SNPs) have focused primarily on the effects of "machine-error", number of replicates, and the size of the pool. We use the non-centrality parameter (NCP) for the analysis of variance test to compute the approximate power for genetic association tests with DNA pooling data on cases and controls. We incorporate genetic model parameters into the computation of the NCP. Parameters involved in the power calculation are disease allele frequency, frequency of the marker SNP allele in coupling with the disease locus, disease prevalence, genotype relative risk, sample size, genetic model, number of pools, number of replicates of each pool, and the proportion of variance of the pooled frequency estimate due to machine variability. We compute power for different settings of number of replicates and total number of genotypings when the genetic model parameters are fixed. Several significance levels are considered, including stringent significance levels (due to the increasing popularity of 100 K and 500 K SNP "chip" data). We use a factorial design with two to four settings of each parameter and multiple regression analysis to assess which parameters most significantly affect power.</p> <p>Results</p> <p>The power can increase substantially as the genotyping number increases. For a fixed number of genotypings, the power is a function of the number of replicates of each pool such that there is a setting with maximum power. The four most significant parameters affecting power for association are: (1) genotype relative risk, (2) genetic model, (3) sample size, and (4) the interaction term between disease and SNP marker allele probabilities.</p> <p>Conclusion</p> <p>For a fixed number of genotypings, there is an optimal number of replicates of each pool that increases as the number of genotypings increases. Power is not substantially reduced when the number of replicates is close to but not equal to the optimal setting.</p

Characteristics of replicated single-nucleotide polymorphism genotypes from COGA: Affymetrix and Center for Inherited Disease Research

Genetic Analysis Workshop 14 provided re-genotyped single-nucleotide polymorphism (SNP) data. Specifically, both Center for Inherited Disease Research (CIDR) and Affymetrix genotyped the same 11,560 SNPs from the Affymetrix GeneChip Mapping 10K Array marker set on the same 184 individuals from the Collaborative Study on the Genetics of Alcoholism database. While the inconsistency rate between CIDR and Affymetrix (two different genotypes for the same subject) was low (0.2%), the non-replication rate (two different genotypes for the same subject or one identified genotype and one missing genotype) was substantial (9.5%). The missing data could be from no-call regions, which is inconsistent with recent recommendations about the use of no-call regions in association tests. In addition, no-call regions would suggest that the actual inconsistency rate is higher than reported. A high inconsistency rate has significant impact on power in related hypothesis tests. In addition, the data are consistent with assumptions made in a recently proposed likelihood ratio test of association for re-genotyped data

TDT-HET: A new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association data

<p>Abstract</p> <p>Background</p> <p>Locus heterogeneity is one of the most documented phenomena in genetics. To date, relatively little work had been done on the development of methods to address locus heterogeneity in genetic association analysis. Motivated by Zhou and Pan's work, we present a mixture model of linked and unlinked trios and develop a statistical method to estimate the probability that a heterozygous parent transmits the disease allele at a di-allelic locus, and the probability that any trio is in the linked group. The purpose here is the development of a test that extends the classic transmission disequilibrium test (<it>TDT</it>) to one that accounts for locus heterogeneity.</p> <p>Results</p> <p>Our simulations suggest that, for sufficiently large sample size (1000 trios) our method has good power to detect association even the proportion of unlinked trios is high (75%). While the median difference (<it>TDT-HET </it>empirical power - <it>TDT </it>empirical power) is approximately 0 for all MOI, there are parameter settings for which the power difference can be substantial. Our multi-locus simulations suggest that our method has good power to detect association as long as the markers are reasonably well-correlated and the genotype relative risk are larger. Results of both single-locus and multi-locus simulations suggest our method maintains the correct type I error rate.</p> <p>Finally, the <it>TDT-HET </it>statistic shows highly significant p-values for most of the idiopathic scoliosis candidate loci, and for some loci, the estimated proportion of unlinked trios approaches or exceeds 50%, suggesting the presence of locus heterogeneity.</p> <p>Conclusions</p> <p>We have developed an extension of the <it>TDT </it>statistic (<it>TDT-HET</it>) that allows for locus heterogeneity among coded trios. Benefits of our method include: estimates of parameters in the presence of heterogeneity, and reasonable power even when the proportion of linked trios is small. Also, we have extended multi-locus methods to <it>TDT-HET </it>and have demonstrated that the empirical power may be high to detect linkage. Last, given that we obtain PPBs, we conjecture that the <it>TDT-HET </it>may be a useful method for correctly identifying linked trios. We anticipate that researchers will find this property increasingly useful as they apply next-generation sequencing data in family based studies.</p