Assessing the influence of organizational personality, applicants' need motivation, expectancy beliefs, and person-organization fit on applicant attraction

This research explored the thesis that organizational personality is related to applicants’ attraction to an organization through a process which involves need motivation, expectancy beliefs, and applicants’ perceptions of person-organization fit. Organizational personality may be defined as a collection of trait-like characteristics that individuals use to describe organizational practices, policies, values, and culture. Specifically, this research investigated the hypothesis that organizational personality information is useful to applicants because it helps individuals to determine their perceptions of fit. A sample of students (N = 198) and working adults (N = 198) participated in an online experiment. Findings indicated that individuals’ beliefs about the instrumentality of desirable work related outcomes are essential to determining their perceptions of fit and organizational attraction. Additionally, organizational personality perceptions interacted with need motivation to affect perceptions of fit and organizational attraction. For instance, perceptions of fit mediated the influence of the interaction between need for achievement and perceptions of innovativeness on organizational attraction. The interaction of need motivation and perceptions of organizational personality helped individuals to better determine their perceptions of fit and subsequent attraction toward organizations.^

Nonnative African jewelfish are more fit but not bolder at the invasion front: a trait comparison across an Everglades range expansion

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Use of Homeostatic Model Assessment Indexes for the Identification of Metabolic Syndrome and Insulin Resistance among Cuban-Americans: A Cross Sectional Study

Aim: to determine cut off points for The Homeostatic Model Assessment Index 1 and 2 (HOMA-1 and HOMA-2) for identifying insulin resistance and metabolic syndrome among a Cuban-American population. Study Design: Cross sectional. Place and Duration of Study: Florida International University, Robert Stempel School of Public Health and Social Work, Department of Dietetics and Nutrition, Miami, FL from July 2010 to December 2011. Methodology: Subjects without diabetes residing in South Florida were enrolled (N=146, aged 37 to 83 years). The HOMA1-IR and HOMA2-IR 90th percentile in the healthy group (n=75) was used as the cut-off point for insulin resistance. A ROC curve was constructed to determine the cut-off point for metabolic syndrome. Results: HOMA1-IR was associated with BMI, central obesity, and triglycerides (P3.95 and >2.20 and for metabolic syndrome were >2.98 (63.4% sensitivity and 73.3% specificity) and >1.55 (60.6% sensitivity and 66.7% specificity), respectively. Conclusion: HOMA cut-off points may be used as a screening tool to identify insulin resistance and metabolic syndrome among Cuban-Americans living in South Florida.

An Alternative Goodness-of-fit Test for Normality with Unknown Parameters

Goodness-of-fit tests have been studied by many researchers. Among them, an alternative statistical test for uniformity was proposed by Chen and Ye (2009). The test was used by Xiong (2010) to test normality for the case that both location parameter and scale parameter of the normal distribution are known. The purpose of the present thesis is to extend the result to the case that the parameters are unknown. A table for the critical values of the test statistic is obtained using Monte Carlo simulation. The performance of the proposed test is compared with the Shapiro-Wilk test and the Kolmogorov-Smirnov test. Monte-Carlo simulation results show that proposed test performs better than the Kolmogorov-Smirnov test in many cases. The Shapiro Wilk test is still the most powerful test although in some cases the test proposed in the present research performs better.