2 resultados para Multiple-regression Analysis

em DigitalCommons@University of Nebraska - Lincoln


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Four of the 12 major Glycine max ancestors of all modern elite U.S.A. soybean cultivars were the grandparents of Harosoy and Clark, so a Harosoy x Clark population would include some of that genetic diversity. A mating of eight Harosoy and eight Clark plants generated eight F1 plants. The eight F1:2 families were advanced via a plant-to-row selfing method to produce 300 F6-derived RILs that were genotyped with 266 SSR, 481 SNP, and 4 classical markers. SNPs were genotyped with the Illumina 1536-SNP assay. Three linkage maps, SSR, SNP, and SSR-SNP, were constructed with a genotyping error of < 1 %. Each map was compared with the published soybean consensus map. The best subset of 94 RILs for a high-resolution framework (joint) map was selected based on the expected bin length statistic computed with MapPop. The QTLs of seven traits measured in a 2-year replicated performance trial of the 300 RILs were identified using composite interval mapping (CIM) and multiple-interval mapping (MIM). QTL x Year effects in multiple trait analysis were compared with results of multiple-interval mapping. QTL x QTL effects were identified in MIM.

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This research examines the impact of a CEO’s statements of aggressiveness on his or her organization’s competitive moves and subsequent performance. Hypotheses were developed based on previous work in Upper Echelon Theory and competitive dynamics. Based on this prior literature, it was hypothesized aggressive statements by CEOs will be associated with more aggressive organizations. It was also hypothesized these more aggressive organizations would display better performance than less aggressive organizations. A content analysis of letters to shareholders and trade publications was performed. This data was analyzed using multiple regression in SPSS 17 to test the hypotheses that aggressive statements by CEOs are associated with aggressive organizations and higher performance. Aggression scores for the content analysis were generated using the software package DICTION. The sample for the study was the organizations with the most revenue in two industries, automobile manufacturing and retailing. Data collection covered a five-year time span from 2003-2007, with performance data lagged one year. Control variables employed included CEO tenure, CEO background, organization size, and organization age. The findings indicate that CEO statements of aggressiveness do not significantly impact the competitive aggressiveness or the performance of their organizations. The implications of these findings are discussed and potential avenues for future research in the area are outlined.