Quadratic Growth Models

2019 ◽  
pp. 79-116
Keyword(s):  
Growth Models ◽  
Quadratic Growth

APPLICATION OF SPC AND GROWTH MODELS ON THE ECONOMIC TRAJECTORY OF THE LEATHER AND FOOTWEAR INDUSTRY

2020 ◽  
Author(s):  
Mario Lesina ◽  
Lovorka Gotal Dmitrovic
Keyword(s):  
Human Capital ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Growth Models ◽  
Pearson Correlation ◽  
Small Companies ◽  
Statistical Process ◽  
Production Staff ◽  
Footwear Industry

The paper shows the relation among the number of small, medium and large companies in the leather and footwear industry in Croatia, as well as the relation among the number of their employees by means of the Spearman and Pearson correlation coefficient. The data were collected during 21 years. The warning zone and the risk zone were determined by means of the Statistical Process Control (SPC) for a certain number of small, medium and large companies in the leather and footwear industry in Croatia. Growth models, based on externalities, models based on research and development and the AK models were applied for the analysis of the obtained research results. The paper shows using the correlation coefficients that The relation between the number of large companies and their number of employees is the strongest, i.e. large companies have the best structured work places. The relation between the number of medium companies and the number of their employees is a bit weaker, while there is no relation in small companies. This is best described by growth models based on externalities, in which growth generates the increase in human capital, i.e. the growth of the level of knowledge and skills in the entire economy, but also deductively in companies on microeconomic level. These models also recognize the limit of accumulated knowledge after which growth may be expected. The absence of growth in small companies results from an insufficient level of human capital and failure to reach its limit level which could generate growth. According to Statistical Process Control (SPC), control charts, as well as regression models, it is clear that the most cost-effective investment is the investment into medium companies. The paper demonstrates the disadvantages in small, medium and large companies in the leather and footwear industry in Croatia. Small companies often emerge too quickly and disappear too easily owing to the employment of administrative staff instead of professional production staff. As the models emphasize, companies need to invest into their employees and employ good production staff. Investment and support to the medium companies not only strengthens the companies which have a well-arranged technological process and a good systematization of work places, but this also helps large companies, as there is a strong correlation between the number of medium and large companies.

Nuances in Alzheimer’s Genetic Risk Reveal Differential Predictions of Non-demented Memory Aging Trajectories: Selective Patterns by APOE Genotype and Sex

2019 ◽  
Vol 16 (4) ◽  
pp. 302-315 ◽  
Author(s):  
G. Peggy McFall ◽  
Lars Bäckman ◽  
Roger A. Dixon
Keyword(s):  
Genetic Risk ◽  
Growth Models ◽  
Memory Performance ◽  
Apoe Genotype ◽  
Cognitively Impaired ◽  
Latent Growth ◽  
Latent Growth Models ◽  
Selective Protection ◽  
Underlying Mechanisms ◽  
Apoe Genotypes

Background: Apolipoprotein E (APOE) is a prominent genetic risk factor for Alzheimer’s disease (AD) and a frequent target for associations with non-demented and cognitively impaired aging. APOE offers a unique opportunity to evaluate two dichotomous comparisons and selected gradations of APOE risk. Some evidence suggests that APOE effects may differ by sex and emerge especially in interaction with other AD-related biomarkers (e.g., vascular health). Methods: Longitudinal trajectories of non-demented adults (n = 632, 67% female, Mage = 68.9) populated a 40-year band of aging. Focusing on memory performance and individualized memory trajectories, a sequence of latent growth models was tested for predictions of (moderation between) APOE and pulse pressure (PP) as stratified by sex. The analyses (1) established robust benchmark PP effects on memory trajectories, (2) compared predictions of alternative dichotomous groupings (ε4- vs ε4+, ε2- vs ε2+), and (3) examined precision-based predictions by disaggregated APOE genotypes. Results: Healthier (lower) PP was associated with better memory performance and less decline. Therefore, all subsequent analyses were conducted in the interactive context of PP effects and sex stratification. The ε4-based dichotomization produced no differential genetic predictions. The ε2-based analyses showed sex differences, including selective protection for ε2-positive females. Exploratory follow-up disaggregated APOE genotype analyses suggested selective ε2 protection effects for both homozygotic and heterozygotic females. Conclusion: Precision analyses of AD genetic risk will advance the understanding of underlying mechanisms and improve personalized implementation of interventions.

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