scholarly journals Towards an early software estimation using log-linear regression and a multilayer perceptron model

2013 ◽  
Vol 86 (1) ◽  
pp. 144-160 ◽  
Author(s):  
Ali Bou Nassif ◽  
Danny Ho ◽  
Luiz Fernando Capretz
Keyword(s):  
Linear Regression ◽  
Multilayer Perceptron ◽  
Software Estimation ◽  
Log Linear

Are seasonal lakes as productive as permanent lakes? A case study from Ireland

2010 ◽  
Vol 67 (8) ◽  
pp. 1291-1302 ◽  
Author(s):  
Helder Cunha Pereira ◽  
Norman Allott ◽  
Catherine Coxon
Keyword(s):  
Seasonal Variation ◽  
Linear Regression ◽  
Chlorophyll A ◽  
Algal Biomass ◽  
P Limitation ◽  
Underlying Causes ◽  
Western Ireland ◽  
Log Linear ◽  
First Time

This paper compares, for the first time, nutrient levels and chlorophyll a measured in a set of seasonal lakes with those reported for permanent lakes in the literature. Twenty-two turloughs (karstic seasonal lakes) in western Ireland were sampled monthly from the onset of flooding (October) until they dried out (6 to 9 months). The turloughs showed similar levels of nutrients and chlorophyll a to those reported for Irish and international lakes. Chlorophyll a peaked between November and February in the majority of turloughs, sometimes with values higher than those measured in mesotrophic lakes in summer. A significant log-linear regression was found between total phosphorus and chlorophyll a, which suggests P limitation of algal biomass in the majority of the turloughs. The regression characteristics were not significantly different than those described in similar studies of permanent lakes. Patterns in seasonal variation of nutrients are also presented, their underlying causes being discussed in relation to their transport within catchments. Our results show that despite being predominantly winter phenomena, turloughs can be as productive as permanent lakes.

scholarly journals How Does Antimicrobial Resistance Increase Medical Costs in Community-Acquired Acute Pyelonephritis?

2021 ◽  
Vol 1 (S1) ◽  
pp. s23-s23
Author(s):  
Bongyoung Kim ◽  
Taul Cheong ◽  
Jungmo Ahn
Keyword(s):  
Antimicrobial Resistance ◽  
Linear Regression ◽  
Acute Pyelonephritis ◽  
Tertiary Care ◽  
Medical Costs ◽  
Hospitalized Patients ◽  
Care Hospital ◽  
Causative Pathogen ◽  
Significant Difference ◽  
Log Linear

Background: The proportion of antimicrobial-resistant Enterobacterales that are causative pathogens for community-acquired acute pyelonephritis (CA-APN) has been increasing. We examined the effect of antimicrobial resistance on medical costs in CA-APN. Methods: A single-center retrospective cohort study was conducted at a tertiary-care hospital in Korea between January 2018 to December 2019. All hospitalized patients aged ≥19 years who were diagnosed with CA-APN were recruited, and those with Enterobacterales as a causative pathogen were included. Comparisons between CA-APN caused by extended-spectrum β-lactamase (ESBL)–producing pathogens (ESBL+ group) and those by non–ESBL-producing organisms (ESBL– group) as well as CA-APN caused by ciprofloxacin-resistant pathogens (CIP-R group) and those by ciprofloxacin-sensitive pathogens (CIP-S group) were performed. Log-linear regression was performed to determine the risk factors for medical costs. Results: In total, 241 patients were included in this study. Of these, 75 (31.1%) had an ESBL-producing pathogen and 87 (36.1%) had a ciprofloxacin-resistant pathogen. The overall medical costs were significantly higher in the ESBL+ group compared with the ESBL− group (US$3,730.18 vs US$3,119.32) P <0.001) as well as in CIP-R group compared with CIP-S group (3,730.18 USD vs. 3,119.32 USD, P =0.005). In addition, length of stay was longer in ESBL+ group compared with ESBL-group (11 vs. 8 days, P <0.001) as well as in CIP-R group compared with CIP-S group (11 vs. 8 days, P <0.001). There were no significant difference in the proportion of clinical failure between ESBL+ and ESBL- groups; CIP-R and CIP-S groups. Based on the log-linear regression model, the costs associated with ESBL-producing Enterobacterales as the causative pathogen would be, on average, 27% higher or US$1,211 higher than its counterpart (P = .026). By the same token, a patient who is a year older would incur US$23 higher cost (P = .040). Having any structural problem in urinary tract would incur US$1,231 higher cost (P = .015). A unit increase in Pitt score would incur US$767 USD higher cost (P < 0.001) higher cost, all other things constant. Conclusions: Medical costs for hospitalized patients with CA-APN are increased by the existence of ESBL-producing Enterobacterales but not by the existence of ciprofloxacin-resistant Enterobacterales.Funding: NoDisclosures: None

Statistical Techniques for Interpreting Body Size–Related Exercise Performance during Growth

2000 ◽  
Vol 12 (2) ◽  
pp. 112-127 ◽  
Author(s):  
Joanne R. Welsman ◽  
Neil Armstrong
Keyword(s):  
Body Size ◽  
Linear Regression ◽  
Body Mass ◽  
Exercise Performance ◽  
Multilevel Regression ◽  
Cross Sectional ◽  
Regression Techniques ◽  
Ontogenetic Allometry ◽  
Log Linear ◽  
Individual Size

This paper reviews some of the statistical methods available for controlling for body size differences in the interpretation of developmental changes in exercise performance. For cross-sectional data analysis simple per body mass ratio scaling continues to be widely used, but is frequently ineffective as the computed ratio remains correlated with body mass. Linear regression techniques may distinguish group differences more appropriately but, as illustrated, only allometric (log-linear regression) scaling appropriately removes body size differences while accommodating the heteroscedasticity common in exercise performance data. The analysis and interpretation of longitudinal data within an allometric framework is complex. More established methods such as ontogenetic allometry allow insights into individual size-function relationships but are unable to describe adequately population effects or changes in the magnitude of the response. The recently developed multilevel regression modeling technique represents a flexible and sensitive solution to such problems allowing both individual and group responses to be modeled concurrently.

E-Government Organizational Performance Framework

2010 ◽  
pp. 144-165
Author(s):  
Susheel Chhabra ◽  
Mahadeo Jaiswal
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Organizational Performance ◽  
State Government ◽  
Linear Regression Analysis ◽  
Performance Framework ◽  
Efficiency And Effectiveness ◽  
Enhance Efficiency ◽  
Log Linear

The objective of this chapter is to design an e-government organizational performance framework and to suggest ICTs solutions through a case study of Haryana state government in India so as to enhance efficiency and effectiveness of services provided to citizens. The framework is suggested using responses collected from 150 government departments. The ICTs solutions were validated by data collected from 90 e-government experts. A log linear regression analysis is used to develop the framework. The framework with minor modifications can be developed for similar other e-government settings.

The Stochastic Disturbance Specification and its Implications for Log-Linear Regression

1979 ◽  
Vol 11 (7) ◽  
pp. 781-790 ◽  
Author(s):  
J M Haworth ◽  
P J Vincent
Keyword(s):  
Spatial Analysis ◽  
Linear Regression ◽  
Conditional Expectation ◽  
Linear Models ◽  
Model Specification ◽  
Stochastic Disturbance ◽  
Log Linear

Model specification is a crucial factor in regression. We show that in log-linear models, although the estimated relationship represents the conditional expectation of ln Y, the antilogarithm does not give the conditional expectation of Y. This has important implications in spatial analysis.

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