Academic literature on the topic 'Fisher's z-transformation'

Over the past decades, numerous experts have been investigated the correlation among distinct personality traits and job performance. However, relatively less attention was paid examining the significance of technological tools in sales management, especially in developing countries. This article explores the relationship among the five-factor model (FFM) of personality traits and sales performance (SP) with a moderating role of the technology. To this end, structural equation modeling and Fisher's Z transformation analysis were employed to analyze the hypotheses. The findings revealed that extraversion, conscientiousness, openness to experience, and emotional stability traits are positively correlated to SP. In contrast, agreeableness is not highly correlated with SP relatively than the remainder traits. Additionally, results revealed the significant effect of technology as a moderator which strengthens the association of FFM and SP. This study proposes diverse managerial implications and future directions for practitioners and academicians across the nations.

This study compares the schema modes between the clinical and non-clinical individuals. A purposive convenient sampling technique was used for the data collection from one hundred and fifty healthy community volunteers, and sixty diagnosed psychiatric patients. The "Schema Mode Inventory (SMI)" was utilized for the mode assessment and group comparison. A series of independent sample t-test depicted that, the clinical group had a significantly higher score on ten out of twelve dysfunctional schema modes and significantly lesser score on both functional schema modes. Identically, Fisher's r-to-z transformation confirmed that the association between dysfunctional schema modes was significantly higher in clinical individuals in comparison to non-clinical individuals. Thus, the present study describes a tendency of individuals with psychiatric disorders to rely more on dysfunctional schema modes in comparison to non-clinical individuals. These findings strengthen the empirical provision of the "schema mode model" for the assessment and treatment of psychiatric disorders.

AbstractAssessing the relationship between antimicrobial usage (AMU) and antimicrobial resistance (AMR) requires the accurate and precise utilisation of register data. Therefore, validation of register-based data is essential for evaluating the quality and, subsequently, the internal validity of studies based on the data.In this study, different smoothing methods for Veterinary Medicine Statistic Program database (VetStat)-records were validated by comparing these with farm-records. Comparison between measurements included accuracy as; completeness and correctness, and precision as; a relative difference of the error, correlation with Fisher's z transformation and reliability coefficient. The most valid methods of those examined were then used in re-analyses of the abundance of AMR genes in 10 finisher batches from a previous study.Improved accuracy was found when detailed smoothing methods were applied. Although the precision also increased, the effect was not as pronounced, as the usage estimate of all smoothing methods deviated moderately compared with the farm-registrations. Applying the most valid methods to the 10 finisher batches increased estimates of statistical model fit for aminoglycosides, lincosamides, tetracyclines and decreased estimates of statistical model fit for macrolides. The estimates of statistical model fit for sulfonamides and broad-spectrum penicillins remained the same.Through refined data transformation, VetStat-records can be used to calculate a daily amount of AMU per pig reflecting the true usage accurately and moderately precisely, which is the foundation for calculating lifetime AMU.

Abstract This paper presents a pilot study on the differences in evoked EEG coherence measures (computed as zero-lagged cross-correlation, “EC”) between chess experts and novices while solving chess problems. One of our earlier investigations ( Volke, 1999 ) had shown that both location and direction of EC changes in task processing (compared with a resting condition) depend on the degree of task performance. As a result we postulated that when solving the same tasks experts and novices would show different EC. The results of the recent study confirmed this supposition. Chess tasks of varying difficulty were presented to 25 chess players of different performance levels. The EEG was recorded from 29 positions (enhanced 10:20-system). EC were computed for post-stimulus intervals of 1.6s. A special averaging procedure (considering Fisher's Z transformation) was applied for summarizing the single EC of each type of task. These subject- and task-related EC-values (29 × 28/2 = 406 values per frequency band) were subjected to a MANOVA after a two-staged principal component analysis. Significant differences between experts and novices, compared with the resting condition, were found in the delta frequency range. The relevant cortical areas of experts, defined by a topological analysis of the differentiating principal components, were located rather posterior and more in the right hemisphere, compared with those of the novices. Furthermore, the essential EC of the experts showed higher values in the task situation (“on-coupling”), compared with the resting condition, whereas those of the novices were lower (“off-coupling”). The results are interpreted as a higher task-related functional integration of the cortical areas in experts.