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Journal articles on the topic 'Stepwise regressions'
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Chang, Shao-Tung, Kang-Ping Lu, and Miin-Shen Yang. "Stepwise possibilistic c-regressions." Information Sciences 334-335 (March 2016): 307–22. http://dx.doi.org/10.1016/j.ins.2015.11.042.
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Hauck, Walter W., and Rei Miike. "A proposal for examining and reporting stepwise regressions." Statistics in Medicine 10, no. 5 (May 1991): 711–15. http://dx.doi.org/10.1002/sim.4780100505.
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Streiner, David L. "Regression in the Service of the Superego: The Do's and Don'ts of Stepwise Multiple Regression." Canadian Journal of Psychiatry 39, no. 4 (May 1994): 191–96. http://dx.doi.org/10.1177/070674379403900401.
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Stepwise multiple regression is a very powerful but often misused technique. It can be used to find a set of independent variables which can predict some outcome. However, there are problems when the results of a stepwise solution are used to try to explain or understand the dependent variable. This paper discusses the different types of stepwise regressions, some of the legitimate and illegitimate uses of this technique, some of the difficulties encountered when trying to interpret the results and other solutions to the problems posed by using them.
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Ray, Supratim, Chandana Sengupta, and Kunal Roy. "QSAR modeling for lipid peroxidation inhibition potential of flavonoids using topological and structural parameters." Open Chemistry 6, no. 2 (June 1, 2008): 267–76. http://dx.doi.org/10.2478/s11532-008-0014-7.
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AbstractIn the present study, Quantitative Structure-Activity Relationship (QSAR) modeling has been carried out for lipid peroxidation (LPO)-inhibition potential of a set of 27 flavonoids, using structural and topological parameters. For the development of models, three methods were used: (1) stepwise regression, (2) factor analysis followed by multiple linear regressions (FA-MLR) and (3) partial least squares (PLS) analysis. The best equation was obtained from stepwise regression analysis (Q2 = 0.626) considering the leave-oneout prediction statistics.
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Guidolin, Massimo, and Manuela Pedio. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns." Forecasting 4, no. 1 (February 18, 2022): 275–306. http://dx.doi.org/10.3390/forecast4010016.
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In this paper, we conduct a thorough investigation of the predictive ability of forward and backward stepwise regressions and hidden Markov models for the futures returns of several commodities. The predictive performance relative a standard AR(1) benchmark is assessed under both statistical and economic loss functions. We find that the evidence that either stepwise regressions or hidden Markov models may outperform the benchmark under standard statistical loss functions is rather weak and limited to low-volatility regimes. However, a mean-variance investor that adopts flexible forecasting models (especially stepwise predictive regressions) when building her portfolio, achieves large benefits in terms of realized Sharpe ratios and mean-variance utility compared to an investor employing AR(1) forecasts.
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Ray, Supratim, Chandana Sengupta, and Kunal Roy. "QSAR modeling of antiradical and antioxidant activities of flavonoids using electrotopological state (E-State) atom parameters." Open Chemistry 5, no. 4 (December 1, 2007): 1094–113. http://dx.doi.org/10.2478/s11532-007-0047-3.
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AbstractIn the present paper QSAR modeling using electrotopological state atom (E-state) parameters has been attempted to determine the antiradical and the antioxidant activities of flavonoids in two model systems reported by Burda et al. (2001). The antiradical property of a methanolic solution of 1, 1-diphenyl-2-picrylhydrazyl (DPPH) and the antioxidant activity of flavonoids in a β-carotenelinoleic acid were the two model systems studied. Different statistical tools used in this communication are stepwise regression analysis, multiple linear regressions with factor analysis as the preprocessing step for variable selection (FA-MLR) and partial least squares analysis (PLS). In both the activities the best equation is obtained from stepwise regression analysis, considering, both equation statistics and predictive ability (antiradical activity: R 2 = 0.927, Q2 = 0.871 and antioxidant activity: R 2 = 0.901, Q2 = 0.841).
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Hornby, T. George, Christopher E. Henderson, Carey L. Holleran, Linda Lovell, Elliot J. Roth, and Jeong Hoon Jang. "Stepwise Regression and Latent Profile Analyses of Locomotor Outcomes Poststroke." Stroke 51, no. 10 (October 2020): 3074–82. http://dx.doi.org/10.1161/strokeaha.120.031065.
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Background and Purpose: Previous data suggest patient demographics and clinical presentation are primary predictors of motor recovery poststroke, with minimal contributions of physical interventions. Other studies indicate consistent associations between the amount and intensity of stepping practice with locomotor outcomes. The goal of this study was to determine the relative contributions of these combined variables to locomotor outcomes poststroke across a range of patient demographics and baseline function. Methods: Data were pooled from 3 separate trials evaluating the efficacy of high-intensity training, low-intensity training, and conventional interventions. Demographics, clinical characteristics, and training activities from 144 participants >1-month poststroke were included in stepwise regression analyses to determine their relative contributions to locomotor outcomes. Subsequent latent profile analyses evaluated differences in classes of participants based on their responses to interventions. Results: Stepwise regressions indicate primary contributions of stepping activity on locomotor outcomes, with additional influences of age, duration poststroke, and baseline function. Latent profile analyses revealed 2 main classes of outcomes, with the largest gains in those who received high-intensity training and achieved the greatest amounts of stepping practice. Regression and latent profile analyses of only high-intensity training participants indicated age, baseline function, and training activities were primary determinants of locomotor gains. Participants with the smallest gains were older (≈60 years), presented with slower gait speeds (<0.40 m/s), and performed 600 to 1000 less steps/session. Conclusions: Regression and cluster analyses reveal primary contributions of training interventions on mobility outcomes in patients >1-month poststroke. Age, duration poststroke, and baseline impairments were secondary predictors. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02507466 and NCT01789853.
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Sapkota, Kamal Raj. "Study on QSPR Method for Theoretical Calculation of Boiling Point of Some organic Compounds." Himalayan Physics 3 (January 1, 2013): 93–95. http://dx.doi.org/10.3126/hj.v3i0.7316.
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Quantitative structure-property relationship (QSPR) models based on molecular descriptors derived from molecular structures have been developed for the prediction of boiling point using a set of 25 organic compounds. The molecular descriptors used to represent molecular structure include topological indices and constitutional descriptors. Forward stepwise regression was used to construct the QSPR models. Multiple linear regressions is utilized to construct the linear prediction model. The prediction result agrees well with the experimental value of these properties.The Himalayan PhysicsVol. 3, No. 3, July 2012Page: 93-95
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Zhang, Ying Chen, Zheng Feng Zhu, Hong Yan Wu, and Yi Ping Qiu. "Optimization Fabrication of Plasma Treated Nano-Titanium Dioxide Particles/PP/PLA Composites Filaments Using Melt Spinning." Materials Science Forum 658 (July 2010): 467–70. http://dx.doi.org/10.4028/www.scientific.net/msf.658.467.
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The Melt spinning technique of Nano-titanium dioxide particles/PP/PLA composites filaments fabricated by plasma treated Nano-titanium dioxide particles studied in the present investigation. The experimental results showed that the physical and mechanical properties of Nano-titanium dioxide particles /PP/PLA composites filaments depended on the following factors of the percentage of Nano-titanium dioxide particles, the percentage of maleic anhydride (MAH), plasma treatment parameters: flow rate of helium gas, output power, sample treatment or stationary time and flow rate of oxygen gas. Among it the flow rate of oxygen gas had the significant influence on the filament properties of tensile modulus, the yield strength and the melting temperature. Stepwise multiple regressions orthogonal design method of system optimization used to determine the percent of contribution of each factor. It found that the three indicators were different by these analyses. The experimental results indicated that the optimized conditions by stepwise multiple regressions were better than that by traditional analysis.
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Zhang, Ying Chen, Hong Yan Wu, and Y. P. Qiu. "Fabrication of Plasma Treated Nano Zinc Oxide/PP/PLA Composites Filaments Using Melt Spinning." Materials Science Forum 610-613 (January 2009): 323–34. http://dx.doi.org/10.4028/www.scientific.net/msf.610-613.323.
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The Melt spinning technique of Nano Zinc Oxide/PP/PLA composites filaments fabricated by plasma treated Nano Zinc Oxide（NZOP） was studied in the present investigation. The experimental results showed that the physical and mechanical properties of Nano Zinc Oxide/PP/PLA composites filaments depended on the following factors of the percentage of NZOP, the percentage of maleic anhydride (MAH), the plasma treatment parameters, helium gas flow rate, output power, sample treatment or stationary time and oxygen gas flow rate. Among them the oxygen gas flow rate had the significant influence on the filament properties of tensile modulus, the yield strength, the melting temperature and the crystallization temperature. Stepwise multiple regressions orthogonal design method of system optimization was used to determine the percent of contribution of each factor. It was found that the four indicators were different by these analyses. The experimental results indicated that the optimized conditions by stepwise multiple regressions were better than that by traditional analysis.
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Barton, K., and R. M. Dreger. "Prediction of Marital Roles from Normal and Pathological Dimensions of Personality: 16 PF and MMPI." Psychological Reports 59, no. 2 (October 1986): 459–68. http://dx.doi.org/10.2466/pr0.1986.59.2.459.
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By means of stepwise multiple regression, 12 factors of the Marriage Role Questionnaire were regressed on factors of the Sixteen Personality Factor Questionnaire and 25 scales of the Minnesota Multiphasic Personality Inventory. The regressions were run with the predictor instruments separately and combined. Individually, the MMPI proved superior to the 16 PF in predicting to the factors of the Marriage Role Questionnaire. However, in six cases out of the 12 predictability improved substantially when both instruments were utilized together. Some of the substantive results of this investigation match findings from previous research.
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Avval, Zhila, Eslam Pourbashir, Mohammad Ganjali, and Parviz Norouzi. "Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors." Journal of the Serbian Chemical Society 80, no. 2 (2015): 187–96. http://dx.doi.org/10.2298/jsc140523064a.
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This paper deals with developing a linear quantitative structure-activity relationship (QSAR) model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-?] indole, diazepino [1,2-?] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR) technique combined with the stepwise (SW) and the genetic algorithm (GA) methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.
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Santos, Maria Céu, Filipe Coelho, Jorge F. S. Gomes, and Carlos M. P. Sousa. "Personal values and the features of psychological contracts." International Journal of Organizational Analysis 27, no. 4 (September 2, 2019): 1111–23. http://dx.doi.org/10.1108/ijoa-08-2018-1507.
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PurposeThis paper aims to investigate how personal values relate to the psychological contract employees establish with their employers.Design/methodology/approachThe sample consisted of 223 frontline employees from a major Portuguese company. The paper used stepwise regressions analysis to test the research hypotheses.FindingsCollectivistic-oriented values were generally related to psychological contract features such as long time frame, lower tangibility, flexibility, inequality and collective regulation. Conversely, individualistic-oriented values were generally associated with a short time frame and a more tangible, stable, equal and individually regulated type of contract with a narrow scope.Research limitations/implicationsThis study uses cross-sectional data collected from a single Portuguese company. While common method bias could potentially affect the results, various procedural remedies were used to control for it. Finally, the study relied on stepwise regression, which is a data-driven approach.Practical implicationsThe study supports the contentions that internal dispositions are related to psychological contracts.Originality/valueThis paper innovates by exploring how employees’ personal values are associated with the psychological contract from a feature-oriented approach. In addition, this study was carried out in Portugal, highlighting the importance of exploring existing models and theories in different cultural contexts.
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Barbosa, Lucas, Caio Sousa, Marcelo Sales, Rafael Olher, Samuel Aguiar, Patrick Santos, Eduard Tiozzo, Herbert Simões, Pantelis Nikolaidis, and Beat Knechtle. "Celebrating 40 Years of Ironman: How the Champions Perform." International Journal of Environmental Research and Public Health 16, no. 6 (March 20, 2019): 1019. http://dx.doi.org/10.3390/ijerph16061019.
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We aimed to determine which discipline had the greater performance improvements in the history of Ironman triathlon in Hawaii and also which discipline had the greater influence in overall race time. Data from 1983 to 2018 of the top three women and men of each year who competed in the Ironman World Championship were included. In addition to exploratory data analyses, linear regressions between split times and years of achievement were performed. Further, a stepwise multiple linear regression was applied using total race time as the dependent variable and split times as the independent variables. Both women and men significantly improved their performances from 1983 to 2018 in the Ironman World Championship. Swimming had the largest difference in improvements between men and women (3.0% versus 12.1%, respectively). A negative and significant decrease in each discipline was identified for both women and men, with cycling being the discipline with the greatest reduction. The results from the stepwise multiple regression indicated that cycling was the discipline with the highest influence on overall race time for both sexes. Based on the findings of this study, cycling seems to be the Ironman triathlon discipline that most improved overall race times and is also the discipline with the greatest influence on the overall race time of elite men and women in the Ironman World Championship.
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Fakorede, M. A. B., and B. O. Opeke. "Weather Factors Affecting the Response of Maize to Planting Dates in a Tropical Rainforest Location." Experimental Agriculture 21, no. 1 (January 1985): 31–40. http://dx.doi.org/10.1017/s0014479700012229.
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SUMMARYSimple linear correlations, stepwise multiple regressions and path-coefficient analyses were used to determine the relation between grain yield of maize (Zea mays L.) and weather factors in a three year study involving several planting dates within each year. Maximum and minimum relative humidity, which demonstrated negative relationships with yield, were the most reliable factors, both directly and indirectly, for predicting yield. Temperature (including accumulated heat units), sunshine hours and total and effective rainfall generally showed negligible direct effects on yield. Potential evaporation, which showed positive correlation, had a negative direct influence on grain yield. We conclude that, whenever possible, path analysis should be used as well as correlation and regression analyses in explaining the complex multiple interactions of yield and weather factors in crop production.
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Ahmad, Azimah, Nur Anisah Mohamed @ A. Rahman, and Zaharah Wahid. "Optimised Reduction of Surgical Gloves Pinholes using Forward Search Method." Sains Malaysiana 50, no. 12 (December 31, 2021): 3733–44. http://dx.doi.org/10.17576/jsm-2021-5012-22.
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This research investigates the factors that affect the existence of pinholes in surgical gloves during the manufacturing process. Since eight factors affect the existence of pinholes in surgical gloves, a two-level fractional factorial design 28-4 was used to study the main effects and the first-order interactions of the multiple variables. Multiple linear regressions are used to model the data. This paper also examines the presence of influential points in the data using the influential measures in linear regression such as Cook’s Distance, DFFITS, DFBETAS, Studentized Residual, Standardized Residual, Hadi's measure, and the robust forward search. The impact of influential points is further assessed through deletion of potential influential points and model selection using adjusted R2, information criterion, and stepwise selection to see whether these influential points significantly improved the existing model.
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Schag, Gavin M., Douglas A. Stow, Philip J. Riggan, and Atsushi Nara. "Spatial-Statistical Analysis of Landscape-Level Wildfire Rate of Spread." Remote Sensing 14, no. 16 (August 16, 2022): 3980. http://dx.doi.org/10.3390/rs14163980.
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The objectives of this study were to evaluate spatial sampling and statistical aspects of landscape-level wildfire rate of spread (ROS) estimates derived from airborne thermal infrared imagery (ATIR). Wildfire progression maps and ROS estimates were derived from repetitive ATIR image sequences collected during the 2017 Thomas and Detwiler wildfire events in California. Three separate landscape sampling unit (LSU) sizes were used to extract remotely sensed environmental covariates known to influence fire behavior. Statistical relationships between fire spread rates and landscape covariates were analyzed using (1) bivariate regression, (2) multiple stepwise regression, (3) geographically weighted regression (GWR), (4) eigenvector spatial filtering (ESF) regression, (5) regression trees (RT), and (6) and random forest (RF) regression. GWR and ESF regressions reveal that relationships between covariates and ROS estimates are substantially non-stationary and suggest that the global association of fire spread controls are locally differentiated on landscape scales. Directional slope is by far the most strongly associated covariate of ROS for the imaging sequences analyzed and the size of LSUs has little influence on any of the covariate relationships.
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Hui, Li, Jiang Zhong-Cheng, Yang Qi-Yong, Yin Hui, and Wang Yue. "Spatial Estimation of Soil Organic Matter in Karst Peak-cluster Depression." Open Civil Engineering Journal 9, no. 1 (October 29, 2015): 1022–27. http://dx.doi.org/10.2174/1874149501509011022.
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In order to enhance the accuracy of spatial estimation of soil organic matter (SOM), spatial predictions of SOM in 0~20 cm depth were conducted in Guohua Ecological Experimental Area of Minister of Land and Resource of the People’s Republic of China. Analysis of multiple linear stepwise regressions showed that the two terrain attributes of relief degree of land surface (RS) and distance from ridge of mountains (DFR) entered into the regression equation. Therefore, RS and DFR were selected as auxiliary variables to predict SOM by MCOK and RK methods. The accuracy of spatial estimation of SOM was compared among methods of ordinary kriging (OK), multivariable cokriging (MCOK) and regression kriging (RK). Results showed that RK and MCOK methods with terrain attributes as auxiliary variables could enhance the accuracy of spatial estimation of SOM, and MCOK method could promote the accuracy notable by 31.33%. This study can provide a new idea and method for evaluation of soil quality in karst areas.
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Binboga, Erdal, Senol Guven, Fatih Çatıkkaş, Onur Bayazıt, and Serdar Tok. "Psychophysiological Responses to Competition and the Big Five Personality Traits." Journal of Human Kinetics 33, no. 1 (June 1, 2012): 187–94. http://dx.doi.org/10.2478/v10078-012-0057-x.
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Psychophysiological Responses to Competition and the Big Five Personality Traits This study examines the relationship between psychophysiological arousal, cognitive anxiety, and personality traits in young taekwondo athletes. A total of 20 male and 10 female taekwondo athletes (mean age = 18.6 years; ± 1.8) volunteered for the study. The Five Factor Personality Inventory and the state scale of the Spielberger State-Trait Anxiety Inventory (STAI) were used to measure personality and cognitive state anxiety. Electrodermal activity (EDA) was measured twice, one day and approximately one hour prior to the competition, to determine psychophysiological arousal. Descriptive statistics, Pearson product-moment correlations, and stepwise regression were used to analyze the data. Several "Big Five" facets were related to the EDA delta scores that were measured both one day and one hour before the competition. Two stepwise regressions were conducted to examine whether personality traits could significantly predict both EDA delta scores. The final model, containing only neuroticism from the Big Five factors, can significantly explain the variations in the EDA delta scores measured one day before the competition. Agreeableness can significantly explain variations in the EDA delta scores measured one hour before the competition. No relationship was found between cognitive anxiety and the EDA delta scores measured one hour before the competition. In conclusion, personality traits, especially agreeableness and neuroticism, might be useful in understanding arousal responses to competition.
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Wu, Xiu, Jinting Zhang, and Daojun Zhang. "Explore Associations between Subjective Well-Being and Eco-Logical Footprints with Fixed Effects Panel Regressions." Land 10, no. 9 (September 3, 2021): 931. http://dx.doi.org/10.3390/land10090931.
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As environmental degradations constantly and directly threaten human well-being, it is imperative to explore the environmental impacts on people’s happy life. This research investigates the association between subjective well-being (SWB) and ecological footprints (EF) through space-time fixed effects panel regressions. EF, as a vital indicator of environmentally sustainable development, plays a vital role in ecological balance. SWB determines the subjective quality of life for humanity. EF-related factors and socio-economic indexes referring to GDP, urbanization rate, income, education, health, political stability, and political voice accountability in 101 countries were captured. Compared with ordinary least square (OLS), stepwise regression (SR) and fixed effects panel regression models (FEPR) exhibited good fitness regardless of the cross-section or longitudinal models due to R2 beyond 0.9. The finding also discloses that EF and health were positively significant to SWB, while income was negatively significant to SWB. EF was an invert u-shaped link to SWB, which met the assumption of EKC. This research provided a model-driven quantitative method to address environmental impacts on people’s quality life of happiness, and opened shared doors for further research of carbon balance and circular economy.
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Miller, Lucy Jane, and Peter G. W. Schouten. "Maternal Education and Preacademic Problems as Predictors of Teachers' Ratings and Self-Concept." Perceptual and Motor Skills 69, no. 2 (October 1989): 607–10. http://dx.doi.org/10.2466/pms.1989.69.2.607.
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The Harter Perceived Competence Scale for Children was used to assess teachers' and children's ratings of perceived competence four years after preschool screening. Stepwise multiple regressions showed that maternal education was a significant predictor of teachers' ratings of children's cognitive competence and conduct. Preschool problem/no-problem status was significantly related to teachers' rating in four of five domains but only related to the children's self-concept of social competence and global self-worth. The present findings support the importance of child-centered information versus socioeconomic status as a predictor of future functioning.
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Athanasopoulos, George, Haiyan Song, and Jonathan A. Sun. "Bagging in Tourism Demand Modeling and Forecasting." Journal of Travel Research 57, no. 1 (February 2, 2017): 52–68. http://dx.doi.org/10.1177/0047287516682871.
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This study introduces bootstrap aggregation (bagging) in modeling and forecasting tourism demand. The aim is to improve the forecast accuracy of predictive regressions while considering fully automated variable selection processes which are particularly useful in industry applications. The procedures considered for variable selection is the general-to-specific (GETS) approach based on statistical inference and stepwise search procedures based on a measure of predictive accuracy (MPA). The evidence based on tourist arrivals from six source markets to Australia overwhelmingly suggests that bagging is effective for improving the forecasting accuracy of the models considered.
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Collin, A., D. James, and E. Feunteun. "TOWARDS BETTER COASTAL MAPPING USING FUSION OF HIGH TEMPORAL SENTINEL-2 AND PLANETSCOPE-2 IMAGERIES: 12 BANDS AT 3 M THROUGH NEURAL NETWORK MODELLING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 479–84. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-479-2022.
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Abstract. Coastal interfaces are subject to an unprecedented rate of risks, gathering waves and rainfalls’ hazards, human assets’ densification, sea-level rise and precipitation intensification. Their sound management requires iterative observation at the highest possible spatial resolution. Sentinel-2 (S-2), provided with 13 spectral bands, datasets leverage high temporal resolution (one week) but spatial resolution (from 60 to 10 m) often remains too coarse to finely classify and monitor the coastal patches. PlanetScope-2 (PS-2) imagery benefits from very high temporal resolution (< one week) and high spatial resolution (3 m) for its blue-green-red-near-infrared dataset.This research paper proposes to, first, downscale 12 S-2 bands (cirrus S10 being evicted) by using neural network (NN) regressions built on the 4 PS-2 bands following two methods, and second, evaluate the NN classification performance of the 12-band datasets at 3 m for mapping 8 common coastal classes on a representative site (Brittany, France). Straightforward and stepwise downscaling procedures, respectively based on 12 and 22 NN regressions, generated very good performances (R2test=0.92 ± 0.02 and 0.95 ± 0.01, respectively). The 3-m NN classifications were considerably improved by the number of spectral bands (overall accuracy, OA, of the 4 bands: 48.12%) but also the precision of the downscaling (OA of the straightforward and stepwise downscaling: 75.25% and 93.57%, respectively). For the best classification, examination of the contribution of the individual bands revealed that S5, S7, S1, S9, S6 and S8A were meaningful (62.42, 55.02, 50.82, 46.4, 45.1, 31.02%, respectively), contrary to S12, S11 and S12 (12.47, 0 and 0%, respectively).
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Lovell, Thomas W. J., Anita C. Sirotic, Franco M. Impellizzeri, and Aaron J. Coutts. "Factors Affecting Perception of Effort (Session Rating of Perceived Exertion) During Rugby League Training." International Journal of Sports Physiology and Performance 8, no. 1 (January 2013): 62–69. http://dx.doi.org/10.1123/ijspp.8.1.62.
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Purpose:The purpose of this study was to examine the validity of session rating of perceived exertion (sRPE) for monitoring training intensity in rugby league.Methods:Thirty-two professional rugby league players participated in this study. Training-load (TL) data were collected during an entire season and assessed via microtechnology (heart-rate [HR] monitors, global positioning systems [GPS], and accelerometers) and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and various other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during rugby league training.Results:There were significant within-individual correlations between sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 62.4% of the adjusted variance in sRPE-TL could be explained by TL measures of distance, impacts, body load, and training impulse (y = 37.21 + 0.93 distance − 0.39 impacts + 0.18 body load + 0.03 training impulse). Furthermore, 35.2% of the adjusted variance in sRPE could be explained by exercise-intensity measures of percentage of peak HR (%HRpeak), impacts/min, m/min, and body load/min (y = −0.01 + 0.37%HRpeak + 0.10 impacts/min + 0.17 m/min + 0.09 body load/min).Conclusion:A combination of internal and external TL factors predicts sRPE in rugby league training better than any individual measures alone. These findings provide new evidence to support the use of sRPE as a global measure of exercise intensity in rugby league training.
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Kao, Yu-Chen, Yin-Ju Lien, Hsin-An Chang, Nian-Sheng Tzeng, Chin-Bin Yeh, and Ching-Hui Loh. "Stigma Resistance in Stable Schizophrenia: The Relative Contributions of Stereotype Endorsement, Self-Reflection, Self-Esteem, and Coping Styles." Canadian Journal of Psychiatry 62, no. 10 (September 8, 2017): 735–44. http://dx.doi.org/10.1177/0706743717730827.
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Objective: Stigma resistance (SR) has recently emerged as a prominent aspect of research on recovery from schizophrenia, partly because studies have suggested that the development of stigma-resisting beliefs may help individuals lead a fulfilling life and recover from their mental illness. The present study assessed the relationship between personal SR ability and prediction variables such as self-stigma, self-esteem, self-reflection, coping styles, and psychotic symptomatology. Method: We performed an exploratory cross-sectional study of 170 community-dwelling patients with schizophrenia. Self-stigma, self-esteem, self-reflection, coping skills, and SR were assessed through self-report. Psychotic symptom severity was rated by the interviewers. Factors showing significant association in univariate analyses were included in a stepwise backward regression model. Results: Stepwise regressions revealed that acceptance of stereotypes of mental illness, self-esteem, self-reflection, and only 2 adaptive coping strategies (positive reinterpretation and religious coping) were significant predictors of SR. The prediction model accounted for 27.1% of the variance in the SR subscale score in our sample. Conclusions: Greater reflective capacity, greater self-esteem, greater preferences for positive reinterpretation and religious coping, and fewer endorsements of the stereotypes of mental illness may be key factors that relate to higher levels of SR. These factors are potentially modifiable in tailored interventions, and such modification may produce considerable improvements in the SR of the investigated population. This study has implications for psychosocial rehabilitation and emerging views of recovery from mental illness.
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Ding, Beidou, Naiqiang Xiao, Shuxun Zhang, and Yong Wang. "Research on NDT Technology in Inference of Steel Member Strength Based on Macro/Micro Model." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4393279.
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In consideration of correlations among hardness, chemical composition, grain size, and strength of carbon steel, a new nondestructive testing technology (NDT) of inferring the carbon steel strength was explored. First, the hardness test, chemical composition analysis, and metallographic analysis of 162 low-carbon steel samples were conducted. Second, the following works were carried out: (1) quantitative relationship between steel Leeb hardness and carbon steel strength was studied on the basis of regression analysis of experimental data; (2) influences of chemical composition and grain size on tension properties of carbon steel were analyzed on the basis of stepwise regression analysis, and quantitative relationship between conventional compositions and grain size with steel strength was obtained; (3) according to the macro and/or micro factors such as hardness, chemical compositions, and grain size of carbon steel, the fitting formula of steel strength was established based on MLR (multiple linear regressions) method. The above relationships and fitting formula based on MLR method could be used to estimate the steel strength with no damage to the structure in engineering practice.
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KIM, JI-WON, YU-RI KWON, HYEONG-MIN JEON, GWANG-MOON EOM, YEONG BIN CHO, and BYUNG KYU PARK. "GENDER-DIFFERENCE IN THE RELATIONSHIP BETWEEN POSTURAL SWAY AND BODY FACTORS DURING QUIET STANDING IN THE ELDERLY." Journal of Mechanics in Medicine and Biology 14, no. 06 (December 2014): 1440008. http://dx.doi.org/10.1142/s0219519414400089.
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The aim of this study was to investigate the relationship between postural sway and body factors (height, weight, and base of support) and their possible gender-difference during quiet standing in elderly subjects. A total of 46 elderly subjects (23 men and 23 women) performed quiet standing in feet-together and natural stances on a force platform. As outcome measures, mean distance (MD), total power (TP), and 95% power frequency were derived from the center of pressure (COP) trajectory. Correlations between body factors and outcome measures were investigated in each gender, and the gender-difference of the correlations was identified. Also, stepwise multiple regressions were performed to recognize the major determinants (among body factors) of the outcome measures in each gender. Significant gender-differences were observed in the correlation of the outcome measures with body factors. In case of the feet-together stance, postural sway size (MD and TP) increased with weight in men, but not in women. In case of the natural stance, 95% power frequency of sway increased with base of support (BOS) in men, but not in women. Stepwise multiple regressions revealed that weight in the feet-together stance and BOS in the natural stance were the major determinants of outcome measures, and that their influence on outcome measures differed between genders. Relationships between postural sway and body factors differed between genders in the elderly. These results suggest that elderly men and women may have different postural control strategies related to body factors and the normalization of the postural sway variables by body factors may not be performed in the same way in elderly men and women.
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FATEMI, MOHAMMAD H., and PARISA IZADIAN. "IN SILICO PREDICTION OF MELTING POINTS OF IONIC LIQUIDS BY USING MULTILAYER PERCEPTRON NEURAL NETWORKS." Journal of Theoretical and Computational Chemistry 11, no. 01 (February 2012): 127–41. http://dx.doi.org/10.1142/s0219633612500083.
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Quantitative structure–property relationship (QSPR) was used to predict melting points of 62 ionic liquids (ILs), which include ammonium, pyrrolidiniu, imidazolium, pyridiniu, piperidiniu, phosphonium ionic liquid salts. The structures of ionic liquids were optimized by Hyperchem software and MOPAC program, and stepwise multiple linear regression method was applied to select the relevant structural descriptors. The predicting models correlating selected descriptors and melting points were set up using multiple linear regressions (MLR) and multilayer perceptron neural network (MLP NN), separately. The obtained linear and nonlinear QSPR models were validated by internal and external test sets. According to the obtained results, the correlation coefficients between predicted and experimental melting points for training, test and validation sets were; 0.91, 0.86 and 0.79 for MLR model. These values for MLP NN model were; 0.97, 0.96 and 0.85, respectively. The results of this study revealed the high applicability of QSPR approach to melting point prediction of ILs.
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Bulik, Cynthia M., Carol A. Prescott, and Kenneth S. Kendler. "Features of childhood sexual abuse and the development of psychiatric and substance use disorders." British Journal of Psychiatry 179, no. 5 (November 2001): 444–49. http://dx.doi.org/10.1192/bjp.179.5.444.
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BackgroundChildhood sexual abuse (CSA) is associated with an increased risk of subsequent psychiatric disorders.AimsTo explore the risk associated with features of CSA and examine whether specific associations exist between particular profiles of CSA and the development of specific syndromes.MethodIn a population-based sample of adult female twins, we used logistic regression to explore the association between features of CSA (reported by the twin and her co-twin) and lifetime major depression, generalised anxiety disorder, bulimia nervosa, panic disorder and alcohol and drug dependence.ResultsIn univariate and stepwise multiple regressions, patterns of predictors differed, although not significantly, across diagnoses. Greater risk was associated with attempted or completed intercourse, the use of force or threats, abuse by a relative, and a negative response by someone who was told about the abuse. Similar patterns were observed with co-twin reports.ConclusionsSpecific features of CSA differentially increase risk of later psychopathology; however, there do not appear to be unique predictive relationships between features of CSA and the emergence of specific psychiatric disorders.
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Baheiraei, Azam, Fatemeh Bakouei, Eesa Mohammadi, Reza Majdzadeh, and Seyed Mostafa Hosseni. "Social capital and related socio-demographic variation in women of reproductive age: A population-based study." International Social Work 61, no. 2 (February 25, 2016): 247–59. http://dx.doi.org/10.1177/0020872815620260.
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In this population-based cross-sectional study of women of reproductive age in Tehran, Iran, the social capital integrated questionnaire and socio-demographic questionnaire were used. The highest mean scores were related to social cohesion and inclusion dimension (55.72 ± 11.94) and the lowest mean scores to groups and networks dimension (31.78 ± 19.43). Stepwise multiple linear regressions showed the significant association between dimensions of social capital and certain socio-demographic variables, particularly family income. Policy makers should help low-income families by designing effective interventions for improving the status of social capital in this group, because it is considered one of the social determinants of health.
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Olaskoaga-Larrauri, Jon, Carlos Mendoza-Sepúlveda, and Elia Marúm-Espinosa. "Concepciones sobre calidad educativa en el profesorado del Sistema de Educación Media Superior de la Universidad de Guadalajara." education policy analysis archives 25 (July 31, 2017): 81. http://dx.doi.org/10.14507/epaa.25.2904.
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This article describes the preferences of the teachers working in the No. 9 School at the High School Education System of the University of Guadalajara, with respect to the different ways of defining the quality of education. This research establishes a relationship between teachers’ adherence to the concepts of quality and their attitudes towards some central features of the Reform of High School Education (RIEMS). We use multiple linear regressions with some dummy variables and stepwise procedures. The conclusions suggest that the teacher´s adherence to certain concepts of quality favourably influences the attitudes of the teachers towards RIEMS and, therefore, facilitates the implementation of this reform.
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Quartezani, Waylson Zancanella, Julião Soares de Souza Lima, Talita Aparecida Pletsch, Evandro Chaves de Oliveira, Sávio da Silva Berilli, Euzileni Mantoanelli, Robson Prucoli Posse, and Luana Mendes Suci. "Multiple linear and spatial regressions to estimate the influence of Latosol properties on black pepper productivity." June 2019, no. 13(06) 2019 (June 20, 2019): 857–62. http://dx.doi.org/10.21475/ajcs.19.13.06.p1424.
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There is little knowledge available on the best techniques for transferring spatial information such as stochastic interpolation and multivariate analyses for black pepper. This study applies multiple linear and spatial regression to estimate black pepper productivity based on physical and chemical properties of the soil. A multiple linear regression including all properties of a Latosol was performed and followed by variance analysis to verify the validity of the model. The adjusted variograms and data interpolation by kriging allowed the use of spatial multiple regression with the properties that were significant in the multiple linear regression. The forward stepwise method was used and the model was validated by the F-test. The influence of the Latosol properties was greater than the residual on the prediction of productivity. The model was composed by the physical properties fine sand (FS), penetration resistance (PR), and Bulk density (BD), and by the chemical properties K, Ca, and Mg (except for Mg in the spatial regression). The physical properties were of greater relevance in determining productivity, and the maps estimated by ordinary kriging and predicted by the spatial multiple regression were very similar in shape.
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Jeffries, Annie C., Lee Wallace, and Aaron J. Coutts. "Quantifying Training Loads in Contemporary Dance." International Journal of Sports Physiology and Performance 12, no. 6 (July 2017): 796–802. http://dx.doi.org/10.1123/ijspp.2016-0159.
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Purpose:To describe the training demands of contemporary dance and determine the validity of using the session rating of perceived exertion (sRPE) to monitor exercise intensity and training load in this activity. In addition, the authors examined the contribution of training (ie, accelerometry and heart rate) and non-training-related factors (ie, sleep and wellness) to perceived exertion during dance training.Methods:Training load and ActiGraphy for 16 elite amateur contemporary dancers were collected during a 49-d period, using heart-rate monitors, accelerometry, and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and several other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during dance training.Results:Average weekly training load was 4283 ± 2442 arbitrary units (AU), monotony 2.13 ± 0.92 AU, strain 10677 ± 9438 AU, and average weekly vector magnitude load 1809,707 ± 1015,402 AU. There were large to very large within-individual correlations between training-load sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 49.7% of the adjusted variance in training-load sRPE was explained by peak heart rate, metabolic equivalents, soreness, motivation, and sleep quality (y = –4.637 + 13.817%HRpeak + 0.316 METS + 0.100 soreness + 0.116 motivation – 0.204 sleep quality).Conclusion:The current findings demonstrate the validity of the sRPE method for quantifying training load in dance, that dancers undertake very high training loads, and a combination of training and nontraining factors contribute to perceived exertion in dance training.
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Mahmoud, B. Y., A. S. Abdel Hafez, A. M. Emam, A. M. Abdelmoniem, and S. A. ElSafty. "Feathering rate impact on growth and slaughter traits of Japanese quail." Journal of Agricultural Science 156, no. 7 (September 2018): 942–48. http://dx.doi.org/10.1017/s0021859618000990.
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AbstractA total of 1180 1-day-old Japanese quail (Coturnix japonica) chicks were used to investigate the effect of feathering rates on growth and slaughter traits. Feathering rates were classified based on the results of stepwise regression using numbers and lengths of both primaries and secondaries and tail length at 7 and 10 days of age as predictors. At 7 and 10 days old, number of primary feathers had phenotypically positive low correlations (rps) with body weight (BW), whereas number of secondaries had positive medium rps with BW at different ages. Lengths of primary, secondary and tail feathers had highly positive rps with BW traits at different ages. Results of stepwise multiple regressions indicated that BW at 14, 21 and 28 days of age can be predicted using lengths of secondary and tail feathers at 10 days old, number of secondaries at 7 days old and length of secondaries at 7 days old, respectively. Body weight at 35 days of age can be predicted using number of primaries,lengths of secondaries and tail at 10 days of age and number of secondaries at 7 days of age. Higher BWs were obtained in the fast-feathering class from 21 up to 35 days of age than in other groups, whereas the slow-feathering class had the lowest BW. Significant class differences were found for carcass weight, feather weight and dressing% favouring the fast- over the slow-feathering class. Therefore, early feathering rates improved BW at later ages and slaughter traits in Japanese quail.
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TORRES, CLÁUDIO V., SOLANGE ALFINITO, CÉSAR AUGUSTO DE SOUZA PINTO GALVÃO, and BRUNA CHIE YIN TSE. "BRAZILIAN JEITINHO VERSUS CHINESE GUANXI: INVESTIGATING THEIR INFORMAL INFLUENCE ON INTERNATIONAL BUSINESS." RAM. Revista de Administração Mackenzie 16, no. 4 (August 2015): 77–99. http://dx.doi.org/10.1590/1678-69712015/administracao.v16n4p77-99.
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ABSTRACTThe Brazilian jeitinho and the Chinese guanxi are considered indigenous forms of informal influence. The first can be described as behavior tactics aimed at resolving social problems. The latter is broadly described as achieving goals through the use of social networks. These influence processes were chosen because they are commonly used in business negotiations in Brazil and China. Thus, understanding their peculiarity is fundamental for the management of organizations involved in business in those two cultures. Therefore, we seek to determine whether such influence processes differ, as it is possible that a process said to be indigenous to a particular cultural context might be, in fact, also found elsewhere. To investigate their uniqueness and the relationship between them, two studies were carried out. In both studies, participants rated representativeness, typicality and positivity of social scenarios, besides completing a 21-item version of the Schwartz’s Portrait Value Survey and a scale regarding attitudes towards corruption. Data were analyzed by a series of mean difference tests and stepwise regressions, separately for each nation, and the results are presented by sample. There were two samples: university students’ sample (with 266 Brazilian and 220 Chinese) and managers’ sample (with 101 Singapore Chinese and 246 Brazilian). Brazil scored significantly higher on conservation and selfenhancement values when compared to China. Chinese respondents perceived the guanxi scenarios as more typical of what happens in China than the jeitinho scenarios, with a reverse pattern being observed for Brazilians. Although Brazilian respondents evaluated jeitinho less positively than Chinese respondents evaluated guanxi scenarios, but they also did perceive jeitinho as more positive than. For the managers’ samples, it was observed that Brazilians had a significantly lower score on attitudes toward business corruptibility when compared to Chinese managers. Stepwise regressions suggest that positivity is linked with business corruptibility for each respective scenario type by nation.
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Li, Gaoyi, Xi Han, Liang Gao, Wusong Tong, Qiang Xue, Shun Gong, Yu Song, Songyu Chen, and Yan Dong. "Association of Anxiety and Depressive Symptoms with Memory Function following Traumatic Brain Injury." European Neurology 84, no. 5 (2021): 340–47. http://dx.doi.org/10.1159/000513195.
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<b><i>Introduction:</i></b> Memory impairment and mood disorders are among the most troubling sequelae following traumatic brain injury (TBI). The relationships between comorbid psychiatric disorders and memory function have not been well illustrated. The aim of the study was to explore the relationships of comorbid anxiety and depressive symptoms with memory function following TBI. <b><i>Methods:</i></b> A total of 46 TBI participants across all levels of injury and 23 healthy controls were enrolled in this case-control study. Wechsler Memory Scale-Chinese Revision (WMS-CR) picture, recognition, associative learning, comprehension memory, and digit span were administered to evaluate several categories of memory capacity. The Hospital Anxiety and Depression Scale (HADS) was employed to evaluate the anxiety and depressive symptoms. Stepwise multiple linear regressions were conducted. <b><i>Results:</i></b> Compared to healthy controls, the participants with TBI reported more anxiety and depressive symptoms. In the meanwhile, they performed more poorly on memory tests, showing 1.84 SDs, 1.07 SDs, and 0.68 SDs below healthy participants on visuospatial memory, working memory, and verbal memory, respectively. A variety of variables, including HADS depression, HADS anxiety, age, GCS, and education were associated with posttraumatic memory function in the bivariate models. The stepwise multiple linear regressions demonstrated a negative association between HADS depression and posttraumatic memory function, especially performance on visuospatial and verbal memory and a positive association between education and posttraumatic memory function. <b><i>Conclusion:</i></b> More depressive symptoms rather than anxiety symptoms and less years of education are significant predictors for posttraumatic memory dysfunction.
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Richardson, Heather J., David J. Hill, Dan R. Denesiuk, and Lauchlan H. Fraser. "A comparison of geographic datasets and field measurements to model soil carbon using random forests and stepwise regressions (British Columbia, Canada)." GIScience & Remote Sensing 54, no. 4 (March 15, 2017): 573–91. http://dx.doi.org/10.1080/15481603.2017.1302181.
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Hennessy, Dwight A., and Stephen Schwartz. "Personal Predictors of Spectator Aggression at Little League Baseball Games." Violence and Victims 22, no. 2 (April 2007): 205–15. http://dx.doi.org/10.1891/088667007780477384.
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Parents from two baseball leagues completed questionnaires regarding their likelihood of engaging in various aggressive behaviors (yelling, swearing, shoving, fighting, humiliating) toward targets at youth baseball games (other spectators, umpires, coaches, other players, their child). Overall, the likelihood of all forms of aggression was very low, particularly physical aggression and swearing. Hierarchical entry stepwise regressions were calculated to determine predictors of yelling and humiliating using demographics, trait aggression, anger, hostility, and vengeance as predictors. Parents with greater hostility reported a greater likelihood of humiliating a child’s teammate, while those with elevated trait anger reported a greater likelihood of yelling at other spectators. Finally, parents with a more vengeful attitude reported a greater likelihood of humiliating umpires.
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Brown, V. E., R. E. Agnew, and D. J. Kilpatrick. "Comparison of methods for prediction of rumen fermentation patterns from diet composition." Proceedings of the British Society of Animal Science 2001 (2001): 27. http://dx.doi.org/10.1017/s1752756200004099.
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Previous attempts (Offer & Percival, 1998) have been made to develop a prediction system for rumen fermentation patterns from stepwise multiple linear regressions of the chemical constituents of the diet. These authors have also made comparisons between equations derived from diet wet chemistry and those developed from near infrared reflectance spectroscopy (NIRS). However, the potential of NIRS to predict the dynamics of rumen fermentation has not fully been explored using a wide range of forage treatments. Therefore the objective of this experiment was to develop equations from the chemical composition of the diet to predict rumen fermentation patterns and compare these with equations developed from undried and dried NIRS scans of the diets.
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Wang, Tingting, Chun’an Tang, Pingfeng Li, Shibin Tang, Minghao Liu, and Bingbing Zhang. "Frost-Heaving Cracking Sensitivity of Single-Flaw Rock Mass Based on a Numerical Experimental Method." Geofluids 2021 (September 14, 2021): 1–13. http://dx.doi.org/10.1155/2021/3436119.
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A novel numerical experimental method is developed herein to study frost-heaving cracking in fractured rock masses by reproducing the physical experimental frost-heaving process. The failure mode of a preexisting closed and water-saturated single-flaw in a rock mass during the frost-heaving process is affected by the inclination angle, flaw width, crack length, and cooling rate. Additionally, a regression model for predicting secondary crack formation and propagation is established by combining multiple stepwise regressions. Overall, the results indicate that preexisting flaw with various inclination angles, flaw lengths, and cooling rates mainly propagates along the flaw-coplanar direction. The secondary crack failure mode is most affected by the flaw width, and the length of the secondary crack increases with increasing inclination angle, flaw width, and flaw length, but decreases with increasing cooling rate. The contributions of the investigated factors to the secondary crack length follow the order: flaw width > inclination angle > cooling rate > flaw length. The results presented herein provide crucial theoretical guidance for engineering and construction projects in cold regions.
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Jin, Jia, and Quan Wang. "Evaluation of Informative Bands Used in Different PLS Regressions for Estimating Leaf Biochemical Contents from Hyperspectral Reflectance." Remote Sensing 11, no. 2 (January 20, 2019): 197. http://dx.doi.org/10.3390/rs11020197.
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Partial least squares (PLS) regression models are widely applied in spectroscopy to estimate biochemical components through hyperspectral reflected information. To build PLS regression models based on informative spectral bands, rather than strongly collinear bands contained in the full spectrum, is essential for upholding the performance of models. Yet no consensus has ever been reached on how to select informative bands, even though many techniques have been proposed for estimating plant properties using the vast array of hyperspectral reflectance. In this study, we designed a series of virtual experiments by introducing a dummy variable (Cd) with convertible specific absorption coefficients (SAC) into the well-accepted leaf reflectance PROSPECT-4 model for evaluating popularly adopted informative bands selection techniques, including stepwise-PLS, genetic algorithms PLS (GA-PLS) and PLS with uninformative variable elimination (UVE-PLS). Such virtual experiments have clearly defined responsible wavelength regions related to the dummy input variable, providing objective criteria for model evaluation. Results indicated that although all three techniques examined may estimate leaf biochemical contents efficiently, in most cases the selected bands, unfortunately, did not exactly match known absorption features, casting doubts on their general applicability. The GA-PLS approach was comparatively more efficient at accurately locating the informative bands (with physical and biochemical mechanisms) for estimating leaf biochemical properties and is, therefore, recommended for further applications. Through this study, we have provided objective evaluations of the potential of PLS regressions, which should help to understand the pros and cons of PLS regression models for estimating vegetation biochemical parameters.
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Shaqrah, Amin A. "Explain the Behavior Intention to Use e-Learning Technologies." International Journal of Web-Based Learning and Teaching Technologies 10, no. 4 (October 2015): 19–32. http://dx.doi.org/10.4018/ijwltt.2015100102.
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The purpose of this study is to explain the behavior intention to use e-learning technologies. In order to achieve a better view and validate the study, researcher attempts to give details of how technology acceptance models help Jordanian trainees firms in accepting e-learning technology, and how if applied will result more attention to usage behavior. Based on the data collected through a survey, stepwise multiple regressions were employed to test the research model. The results revealed that model which developed based on Unified Theory of Acceptance and Use of Technology” UTAUT” indicates that the Jordanian trainees' firms' behavior intention of e- learning technologies is positive affects by performance expectancy; effort expectancy; web-based training infrastructure; trust; culture; and behavioral intention. Managerial implications are further discussed.
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Ekselius, Lisa, and Lars Von Knorring. "Changes in personality traits during treatment with sertraline or Citalopram." British Journal of Psychiatry 174, no. 5 (May 1999): 444–48. http://dx.doi.org/10.1192/bjp.174.5.444.
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BackgroundRecent studies indicate that selective serotonin re-uptake inhibitors (SSRIs) reduce the symptoms accompanying personality disorders and modulate a normal personality.AimsTo examine the effect of two SSRIs, sertraline and Citalopram, on personality traits in major depressed patients.MethodPersonality traits were evaluated at baseline and after six months using the Karolinska Scales of Personality (KSP).ResultsAfter treatment, significant changes in the direction of normalisation were seen in all scales. To determine whether the observed changes could be explained by improved depressive symptoms, multiple stepwise regressions with the separate KSP as dependent variables were performed. Improvements in depressive symptoms only accounted for 0–8.4% of the observed variance.ConclusionsIn depressed patients treated with SSRIs significant effects are seen on personality traits measured by the KSP.
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Anderson, Sally Rose, Amanda Bowen, Glenn Tootle, and Abdoul Oubeidillah. "RECONSTRUCTIONS OF HYDROLOGIC VARIABLES IN THE NORTH PLATTE RIVER BASIN." International Journal of Engineering Technologies and Management Research 6, no. 2 (March 24, 2020): 59–71. http://dx.doi.org/10.29121/ijetmr.v6.i2.2019.356.
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Reconstructions of hydrologic variables are commonly created using tree-ring chronologies (TRCs) to generate information about historic climate and potential future variability. This study used TRCs to reconstruct annual streamflow, April 1st Snow Water Equivalent (SWE), and soil moisture in the North Platte River Basin (NPRB). Stepwise linear regression was performed to determine which of the 55 moisture sensitive TRCs were the best predictors of hydrologic variation. The regressions explained 63% of the variability in streamflow, 55% of the variability in SWE, and 66% of the variability in soil moisture. This study then maximized the overlapping period of records which resulted in a decrease in the percent of variability explained but indicated that the regression models were stable for long reconstruction periods. This study successfully reconstructed all three hydrologic variables for NPRB to 1438 or earlier. Temporal wet and dry periods for streamflow and SWE were closely aligned while soil moisture did not follow similar temporal patterns. This was likely due to a natural “lag” between soil moisture and streamflow / SWE given soil moisture tends to retain antecedent signals. The availability of reconstructed hydrologic data in NPRB allows for a better understanding of the long-term hydrologic variability in the region.
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Jiang, Fugen, Mykola Kutia, Arbi J. Sarkissian, Hui Lin, Jiangping Long, Hua Sun, and Guangxing Wang. "Estimating the Growing Stem Volume of Coniferous Plantations Based on Random Forest Using an Optimized Variable Selection Method." Sensors 20, no. 24 (December 17, 2020): 7248. http://dx.doi.org/10.3390/s20247248.
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Forest growing stem volume (GSV) reflects the richness of forest resources as well as the quality of forest ecosystems. Remote sensing technology enables robust and efficient GSV estimation as it greatly reduces the survey time and cost while facilitating periodic monitoring. Given its red edge bands and a short revisit time period, Sentinel-2 images were selected for the GSV estimation in Wangyedian forest farm, Inner Mongolia, China. The variable combination was shown to significantly affect the accuracy of the estimation model. After extracting spectral variables, texture features, and topographic factors, a stepwise random forest (SRF) method was proposed to select variable combinations and establish random forest regressions (RFR) for GSV estimation. The linear stepwise regression (LSR), Boruta, Variable Selection Using Random Forests (VSURF), and random forest (RF) methods were then used as references for comparison with the proposed SRF for selection of predictors and GSV estimation. Combined with the observed GSV data and the Sentinel-2 images, the distributions of GSV were generated by the RFR models with the variable combinations determined by the LSR, RF, Boruta, VSURF, and SRF. The results show that the texture features of Sentinel-2’s red edge bands can significantly improve the accuracy of GSV estimation. The SRF method can effectively select the optimal variable combination, and the SRF-based model results in the highest estimation accuracy with the decreases of relative root mean square error by 16.4%, 14.4%, 16.3%, and 10.6% compared with those from the LSR-, RF-, Boruta-, and VSURF-based models, respectively. The GSV distribution generated by the SRF-based model matched that of the field observations well. The results of this study are expected to provide a reference for GSV estimation of coniferous plantations.
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Arvin, Babak, Sukhvinder Kalsi-Ryan, Alina Karpova, David Mercier, Julio C. Furlan, Eric M. Massicotte, and Michael G. Fehlings. "Postoperative Magnetic Resonance Imaging Can Predict Neurological Recovery After Surgery for Cervical Spondylotic Myelopathy: A Prospective Study With Blinded Assessments." Neurosurgery 69, no. 2 (April 5, 2011): 362–68. http://dx.doi.org/10.1227/neu.0b013e31821a418c.
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Abstract BACKGROUND: Factors that can predict the recovery of cervical spondylotic myelopathy (CSM) patients postoperatively are of significant interest to physicians and patients and their families. Magnetic resonance imaging (MRI) scans are a common method of examination after surgery, and thus of interest as a predictor of outcome. OBJECTIVE: To investigate whether findings on MRI at 6 months postoperatively could predict recovery at 1 year in CSM patients. METHODS: In 52 consecutive prospective patients, MRI was performed preoperatively and 6 months postoperatively. T1 and T2 signal change (area, height, and segmentation) and spinal cord re-expansion were measured. Outcome measures evaluated at 1 year postoperatively were compared with preoperative values. Univariate and stepwise multiple regressions were undertaken. RESULTS: Using univariate analysis, patients whose cord failed to re-expand had poorer outcome according to the modified Japanese Orthopedic Association score and Nurick score (P = .014) and grip test (P = .006) postoperatively. Stepwise multivariate regression showed lack of cord re-expansion to be predictive of prognosis postoperatively in the modified Japanese Orthopedic Association score (P = .013) and Berg Balance Scale (P = .014), and walking test (P = .011). Postoperative hyperintense T2 signal change was predictive of worse outcome on the Berg Balance Scale (P = .014) and walking test (P = .020), Nurick score (P = .001), and Short Form-36 scores (P = .020). In cases in which the T2 signal intensified, there was a poorer outcome on Nurick scores (P = .013), grip test (P = .017), and Short Form-36 scores (P = .030). CONCLUSION: Findings on postoperative MRI at 6 months is of predictive value in determining outcomes in CSM patients. The persistence and type of T2 signal change and lack of re-expansion of the cord correlate with poorer recovery and likely reflect irreversible structural changes in the spinal cord.
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Oliveira, Alexandre Ferreira, and Luiz A. Joia. "Call Center Operational Performance Indicators and Customer Satisfaction." International Journal of Information Systems in the Service Sector 3, no. 2 (April 2011): 13–31. http://dx.doi.org/10.4018/jisss.2011040102.
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This article purports to investigate the relationship – in an empirical way – between the various operational indicators currently used for the management of call centers in Brazil and customer satisfaction. In this context, a set of call centers rendering services to a telecommunications company will be analyzed in order to verify which of their indicators are positively associated with customer satisfaction. A methodological approach based on surveys as well as stepwise multiple linear regressions is developed and applied in order to achieve the objective of this paper. The “First-Contact Resolution Rate” and the “Average Handle Time After the Call” indicators present a statistically significant relationship with customer satisfaction. Some alternative call center operational performance indicators are proposed, in an exploratory way, so as to convey an enhanced relationship between call center performance and customer satisfaction.
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Conner, Norma E. "Predictive Factors of Hospice Use Among Blacks." American Journal of Hospice and Palliative Medicine® 29, no. 5 (November 8, 2011): 368–74. http://dx.doi.org/10.1177/1049909111425227.
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The purpose of this prospective, correlational study was to examine the differential ability of demographic variables, beliefs, and values about end-of-life, spirituality, and social relationships to predict hospice use among blacks. The framework for this study was the Behavioral Model of Health Services Use. Data were collected from 104 terminally ill black men and women recruited from 6 inpatient and outpatient settings. Only 34% of the individuals participated in hospice services. Chi-square, sequential, and stepwise logistic regressions revealed that the best predictive model consisted of presence of a caregiver, having a religious affiliation, and male gender. Together these factors predicted 13.7% to 19% of hospice use among blacks. Health care providers can use these findings in planning care for patients early in their disease trajectory.
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Guo, Li Ping, Lei Wang, and Yi Min Zhang. "Evaluation of Thixotropic Models of Waxy Crude." Advanced Materials Research 581-582 (October 2012): 85–88. http://dx.doi.org/10.4028/www.scientific.net/amr.581-582.85.
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Thixotropy, which is an important rheological behavior of waxy crudes, is very important to the hydraulic characteristics and safety of the restart process of crude oil pipelines. Thixotropic behaviors of four waxy crudes were studied experimentally under three kinds of loading conditions, which were constant shear rate, stepwise increase of shear rate and cyclic change of shear rate, namely hysteresis loop. Eight thixotropic models were evaluated by least-square regressions based on experimental data. The average absolute deviation was taken as the measurement of fitness of a model. It is concluded that the model, which was established on the basis of Houska model and Cheng’s idea that wax crude oil contains both complete and partial reversibility structures, is the most suitable model to describe the thixotropy of wax crude oil
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Fulthorpe, Roberta R., and J. E. Paloheimo. "Hypolimnetic Oxygen Consumption in Small Lakes." Canadian Journal of Fisheries and Aquatic Sciences 42, no. 9 (September 1, 1985): 1493–500. http://dx.doi.org/10.1139/f85-187.
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The hypolimnetic oxygen consumption rates of 28 Ontario lakes were calculated and compared with lake morphology, chemical concentrations, and productivity measures. In most cases, hypolimnia had upper zones where average light intensities were greater than 1% of surface light. In these layers, oxygen dynamics were highly variable from year to year and production rather than consumption was common. The ratio of areal oxygen consumption below the 1% light level to planktonic production corrected for retention was studied as a measure of percent available material decomposed. Using stepwise multiple regressions, we found this parameter to be related to mean thickness of the hypolimnion, lake organic carbon, and iron concentrations. The range of lake productivities in the data set was small and did not explain a significant portion of the variance in areal hypolimnetic depletion rates.