Search results for: predictors

Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: K. Masingboon, S. Duangpaeng, N. Chaiwong

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Acute myocardial infarction (AMI) is the most common cause of death among Thai with coronary heart disease (CHD). Thai AMI survivors are most likely to have impaired health-related quality of life (HRQoL) due to their lifestyle, functional, and psychological problems. Guided by the Individual and Family Self-Management Theory, this study aimed to explore HRQoL and identify its predictors among Thai AMI survivors. 155 Thai AMI survivors were recruited by stratified random sampling from three hospitals located in eastern region of Thailand. HRQol was measured using the Short Form -12 Health Survey (SF-12). The Center for Epidemiologic studies Depression Scale (CES-D) was utilized to assess the presence of depression, and the Family Support questionnaire was administered to examine family support. Results revealed that 92 percent of Thai AMI survivors reported a generally high level of HRQoL and 80 percent of them reported higher level of HRQoL in physical health and mental health dimension. Depression and family support were significantly predicted HRQoL among Thai AMI survivors and accounted for 28.5 percent of variance (p < .001). Interestingly, depression was the most significant predictors of HRQoL (β = -.65, p < .001) In conclusion, depression is a significant predictor of HRQoL in Thai AMI survivors. Increasing awareness of depression among these survivors is important. Depressive symptoms in should be routinely assessed. In addition, intervention to improve HRQoL among Thai AMI survivors should be addressed through depressive symptom management and family collaboration.

Keywords: health-related quality of life, AMI survivors, predictors, collaboration

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Authors: Ibtisam Al-Zaru

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Background: Worldwide, depression among coronary artery disease (CAD) patients is considered a serious problem that may cause many complications and negative consequences; particularly serious being increased mortality and morbidity rate. Studying depression among CAD patients in Jordan has not been investigated thoroughly and thus a need for further studies has been a priority. Aims: To assess depression in non-hospitalized Jordanian patients with CAD; to describe the relationship between socio-demographic data, health related factors, and depression; and to examine the best predictors of depression in non-hospitalized Jordanian patients with CAD. Method: A cross-sectional-descriptive design was used to collect data from 174 non-hospitalized Jordanian patients diagnosed with CAD in outpatients’ cardiac clinics, using a self- administered questionnaires and Cardiac Depression Scale. Results: 53.4% of CAD patients reported mild/moderate, and severe depressive symptoms. Significant relationships between depressive symptoms and some demo-clinical characteristics (i.e. being female gender; having of chronic disease and surgical history; being physically inactive, and perceived their sexual activity, physical and psychological as poor). The preceding factors are also found to be statistically significant predictors for depression among this patients’ group. Conclusion: Jordanian patients with CAD had various levels of severity regarding their depressive symptoms. Therefore, health care providers need to introduce depression assessment and treatment in cardiac rehabilitation to control depression and its impact on the patient. Consequently, such control will reduce co-morbidity, mortality, complications and health costs among CAD patients and enhance the quality of their lives.

Keywords: coronary artery disease, predictors, depression, prevalence

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Authors: Getahun Nigusie Demise

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Background; antiretroviral treatment reduce HIV-related morbidity, and prolonged survival of patients however, there is lack of up-to-date information concerning the treatment long term effect on the survival of HIV positive children especially in the study area. Objective: The aim of this study is to assess the incidence and predictors of mortality among HIV positive children on antiretroviral therapy (ART) in public hospitals of Harer town who were enrolled from 2011 to 2021. Methodology: Institution based retrospective cohort study was conducted among 429 HIV positive children enrolled in ART clinic from January 1st 2011 to December30th 2021. Data were collected from medical cards by using a data extraction form, Descriptive analyses were used to Summarized the results, and life table was used to estimate survival probability at specific point of time after introduction of ART. Kaplan Meier survival curve together with log rank test was used to compare survival between different categories of covariates, and Multivariate Cox-proportional hazard regression model was used to estimate adjusted Hazard rate. Variables with p-values ≤0.25 in bivariable analysis were candidates to the multivariable analysis. Finally, variables with p-values < 0.05 were considered as significant variables. Results: The study participants had followed for a total of 2549.6 child-years (30596 child months) with an overall mortality rate of 1.5 (95% CI: 1.1, 2.04) per 100 child-years. Their median survival time was 112 months (95% CI: 101–117). There were 38 children with unknown outcome, 39 deaths, and 55 children transfer out to different facility. The overall survival at 6, 12, 24, 48 months were 98%, 96%, 95%, 94% respectively. being in WHO clinical Stage four (AHR=4.55, 95% CI:1.36, 15.24), having anemia(AHR=2.56, 95% CI:1.11, 5.93), baseline low absolute CD4 count (AHR=2.95, 95% CI: 1.22, 7.12), stunting (AHR=4.1, 95% CI: 1.11, 15.42), wasting (AHR=4.93, 95% CI: 1.31, 18.76), poor adherence to treatment (AHR=3.37, 95% CI: 1.25, 9.11), having TB infection at enrollment (AHR=3.26, 95% CI: 1.25, 8.49),and no history of change their regimen(AHR=7.1, 95% CI: 2.74, 18.24), were independent predictors of death. Conclusion: more than half of death occurs within 2 years. Prevalent tuberculosis, anemia, wasting, and stunting nutritional status, socioeconomic factors, and baseline opportunistic infection were independent predictors of death. Increasing early screening and managing those predictors are required.

Keywords: human immunodeficiency virus-positive children, anti-retroviral therapy, survival, treatment, Ethiopia

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Authors: Ekele Alih, Enejo Jalija

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Female Genital Mutilation (FGM) is made up of three types namely: Clitoridectomy, Excision and Infibulation. In this study, we examine the factors responsible for FGM in order to identify the causality variables in a logistic regression approach. From the result of the survey conducted by the Public Health Division, Nigeria Institute of Medical Research, Yaba, Lagos State, the tau statistic, τ was used to screen 9 factors that causes FGM in order to select few of the predictors before multiple regression equation is obtained. The need for this may be that the sample size may not be able to sustain having a regression with all the predictors or to avoid multi-collinearity. A total of 300 respondents, comprising 150 adult males and 150 adult females were selected for the household survey based on the multi-stage sampling procedure. The tau statistic,

Keywords: female genital mutilation, logistic regression, tau statistic, African society

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Authors: Srinaath Anbu Durai, Wang Zhaoxia

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Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

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Authors: Maher El-Masri, Jamie Crawley, Judy Bornais, Abeer Omar

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Background: Misuse of Emergency Department (ED) for non-urgent healthcare results in unnecessary crowdedness that can result in long ED waits and delays in treatment, diversion of ambulances to other hospitals, poor health outcomes for patients, and increased risk of death Objectives: The main purpose of this study was to explore the independent predictors of non-urgent ED visits in Erie St. Clair LHIN. Secondary purposes of the study include comparison of the rates of non-urgent ED visits between urban and rural hospitals Design: A secondary analysis of archived population-based data on 597,373 ED visits in southwestern Ontario Results The results suggest that older (OR = .992; 95% CI .992 – .993) and female patients (OR = .940; 95% CI .929 - .950) were less likely to visit ED for non-urgent causes. Non-urgent ED visits during the winter, spring, and fall were 13%, 5.8%, and 7.5%, respectively, lesser than they were during the summer time. The data further suggest that non-urgent visits were 19.6% and 21.3% less likely to occur in evening and overnight shifts compared to the day shift. Non-urgent visits were 2.76 times more likely to present to small community hospitals than large community hospitals. Health care providers were 1.92 times more likely to refer patients with non-urgent health problem to the ED than the decision taken by patients, family member or caretakers. Conclusion: In conclusion, our study highlights a number of important factors that are associated with inappropriate use of ED visits for non-urgent health problems. Knowledge of these factors could be used to address the issue of unnecessary ED crowdedness.

Keywords: emergency department, non-urgent visits, predictors, logistic regression

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Authors: Shielilo R. Amihan, Ederliza De Jesus

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The study determined the predictors of college performance of 2nd Yr students of UPHSD-Calamba. This quantitative study conducted a survey using the Scholastic Abilities Test for Adults (SATA), and the retrieval of entrance examinations results and current General Weighted Average (GWA) of the 242 randomly selected respondents. The mean, Pearson r and multiple regression analyses through SPSS revealed that students are capable of verbal, non-verbal and quantitative reasoning, reading vocabulary, comprehension, math calculation, and writing mechanics but have difficulty in math application and writing composition. The study found out the Scholastic Ability and Achievement, except in mathematics, are significantly related to college performance. It concludes that students with high ability and achievement may perform better in college. However, only English subset results in the entrance exam predicts the academic success of students in college while SATA and Math entrance exam results do not. The study recommends providing pre-college Math and Writing courses as requisites in college. It also suggests implementing formative curriculum-based enhancement programs on specific priority areas, profiling programs towards informed individual academic decision-making, revising the Entrance Examinations, monitoring the development of the students, and exploring other predictors of college academic performance such as non-cognitive factors.

Keywords: scholastic ability, scholastic achievement, entrance exam, college performance

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Authors: Najib Ahmad Marzuki, Che Su Mustaffa, Johana Johari, Nur Haffiza Rahaman

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The purpose of this paper is to examine the effects and relationship of stress and social support towards the quality of life among flood victims in Malaysia. A total of 764 respondents took part in the survey via random sampling. The depression, anxiety, and stress scales were utilized to measure stress while The Multidimensional Scale of Perceived Social Support was used to measure the quality of life. The findings of this study indicate that there were significant correlations between variables in the study. The findings show a significant negative relation between stress and quality of life, and significant positive correlations between support from family as well as support from friends with the quality of life. Stress and support from family were found to be significant predictors and influences the quality of life among flood victims.

Keywords: stress, social support, quality of life, flood victims

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Authors: E. Botchway, C. Godfrey, V. Anderson, C. Catroppa

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Introduction: Sleep disturbances are common after childhood traumatic brain injury (TBI). This systematic review aimed to assess the prevalence, types, and predictors of sleep disturbances in childhood TBI. Methods: Medline, Pubmed, PsychInfo, Web of Science, and EMBASE databases were searched. Out of the 547 articles assessed, 15 met selection criteria for this review. Results: Sleep disturbances were common in children and adolescents with TBI, irrespective of injury severity. Excessive daytime sleepiness and insomnia were the most common sleep disturbances reported. Sleep disturbance was predicted by sex, injury severity, pre-existing sleep disturbances, younger age, pain, and high body mass index. Conclusions: Sleep disturbances are highly prevalent in childhood TBI, regardless of the injury severity. Routine assessment of sleep in survivors of childhood TBI is recommended.

Keywords: traumatic brain injury, sleep diatiurbances, childhood, systematic review

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Authors: Bin Liu

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Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

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Authors: Ali Kassem, Yaser Kamal, Mohamed Abdel Wahab, Mohamed Hussen

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Introduction: Atherosclerosis is one of the leading causes of death all over the world. Recently, there is an increasing interest in Carotid Intima-Medial Thickness (CIMT) and Ankle Brachial Index (ABI) as non-invasive tools for identifying subclinical atherosclerosis. We aim to examine the role of CIMT and ABI as predictors of the severity of angiographically documented coronary artery disease (CAD). Methods: A cross-sectional study conducted on 60 patients who were investigated by coronary angiography at Sohag University Hospital, Egypt. CIMT: After the carotid arteries were located by transverse scans, the probe was rotated 90 ° to obtain and record longitudinal images of bilateral carotid arteries ABI: Each patient was evaluated in the supine position after resting for 5 min. ABI was measured in each leg using a Doppler Ultrasound while the patient remained in the same position. The lowest ABI obtained for either leg was taken as the ABI measurement for the patient. Results: Patients with carotid mean IMT ≥ 0.9 mm had significantly more severe coronary artery disease than patients without thickening (mean IMT > 0.9 mm). Similarly, patients with low ABI (< 0.9) had significantly more severe coronary artery disease than patients with ABI ≥ 0.9. When the patients were divided into 4 groups (group A, n = 15, mean IMT < 0.9 mm, ABI ≥ 0.9; group B, n = 25, mean IMT < 0.9 mm, low ABI; group C, n = 5, mean IMT ≥ 0.9 mm, ABI ≥ 0.9; group D, n = 19, mean IMT ≤ 0.9 mm, low ABI), the presence of significant coronary stenosis (> 50%) of the groups were significantly different (group A, n = 5: (33.3%); group B, n = 11: (52.4%); group C, n = 4: (60%); group D, n=15, (78.9%), P = 0.001). Conclusion: CIMT and ABI provide useful information on the severity of CAD. Early and aggressive intervention should be considered in patients with CAD and abnormalities in one or both of these non-invasive modalities.

Keywords: ankle brachial index, carotid intima media thickness, coronary artery disease, predictors of severity

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Authors: Adeyemi Adeyinka, Yemisi Ilesanmi

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This study investigated parental involvement and motivation as predictors of students’ learning outcomes in value concepts in Yoruba language in Ibadan, Nigeria. Value concepts in Yoruba language aimed at teaching moral lessons and transmitting Yoruba culture. However, feelers from schools and the society reported students’ poor achievement in examinations and negative attitude to the subject. Previous interventions focused on teaching strategies with little consideration for student-related factors. The study was anchored on psychosocial learning theory. The respondents were senior secondary II students with mean age of 15.50 ± 2.25 from 20 public schools in Ibadan, Oyo-State. In all, 1000 students were selected (486 males and 514 females) through proportionate to sample size technique. Instruments used were Students’ Motivation (r=0.79), Parental Involvement (r=0.87), and Attitude to Yoruba Value Concepts (r=0.94) scales and Yoruba Value Concepts Achievement Test (r=0.86). Data were analyzed using descriptive statistics, Pearson product moment correlation and Multiple regressions at 0.05 level of significance. Findings revealed a significant relationship between parental involvement (r=0.54) and students’ achievement in and attitude to (r=0.229) value concepts in Yoruba. The composite contribution of parental involvement and motivation to students’ achievement and attitude was significant, contributing 20.3% and 5.1% respectively. The relative contributions of parental involvement to students’ achievement (β = 0.073; t = 1.551) and attitude (β = 0.228; t = 7.313) to value concepts in Yoruba were significant. Parental involvement was the independent variable that strongly predicts students’ achievement in and attitude to Yoruba value concepts. Parents should inculcate indigenous knowledge in their children and support its learning at school.

Keywords: parental involvement, motivation, predictors, learning outcomes, value concepts in Yoruba

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Authors: Nataša Šarlija, Sanja Pfeifer

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This study analyzes the innovative orientation of the Croatian entrepreneurs. Innovative orientation is represented by the perceived extent to which an entrepreneur’s product or service or technology is new, and no other businesses offer the same product. The sample is extracted from the GEM Croatia Adult Population Survey dataset for the years 2003-2013. We apply descriptive statistics, t-test, Chi-square test and logistic regression. Findings indicate that innovative orientations vary with personal, firm, meso and macro level variables, and between different stages in entrepreneurship process. Significant predictors are occupation of the entrepreneurs, size of the firm and export aspiration for both early stage and established entrepreneurs. In addition, fear of failure, expecting to start a new business and seeing an entrepreneurial career as a desirable choice are predictors of innovative orientation among early stage entrepreneurs.

Keywords: multilevel determinants of the innovative orientation, Croatian early stage entrepreneurs, established businesses, GEM evidence

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Authors: A. F. Jaber, E. Dean, M. Liu, J. He, D. Sabata, J. Radel

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Background: Stroke is a serious health care concern and a major cause of disability in the United States. This condition impacts the individual’s functional ability to perform daily activities. Predicting functional performance of people with stroke assists health care professionals in optimizing the delivery of health services to the affected individuals. The purpose of this study was to identify significant predictors of Motor FIM and of Cognitive FIM subscores among individuals with stroke after discharge from inpatient rehabilitation (typically 4-6 weeks after stroke onset). A second purpose is to explore the relation among personal characteristics, health status, and functional performance of daily activities within 2 weeks of stroke onset. Methods: This study used a retrospective chart review to conduct a secondary analysis of data obtained from the Healthcare Enterprise Repository for Ontological Narration (HERON) database. The HERON database integrates de-identified clinical data from seven different regional sources including hospital electronic medical record systems of the University of Kansas Health System. The initial HERON data extract encompassed 1192 records and the final sample consisted of 207 participants who were mostly white (74%) males (55%) with a diagnosis of ischemic stroke (77%). The outcome measures collected from HERON included performance scores on the National Institute of Health Stroke Scale (NIHSS), the Glasgow Coma Scale (GCS), and the Functional Independence Measure (FIM). The data analysis plan included descriptive statistics, Pearson correlation analysis, and Stepwise regression analysis. Results: significant predictors of discharge Motor FIM subscores included age, baseline Motor FIM subscores, discharge NIHSS scores, and comorbid electrolyte disorder (R2 = 0.57, p <0.026). Significant predictors of discharge Cognitive FIM subscores were age, baseline cognitive FIM subscores, client cooperative behavior, comorbid obesity, and the total number of comorbidities (R2 = 0.67, p <0.020). Functional performance on admission was significantly associated with age (p < 0.01), stroke severity (p < 0.01), and length of hospital stay (p < 0.05). Conclusions: our findings show that younger age, good motor and cognitive abilities on admission, mild stroke severity, fewer comorbidities, and positive client attitude all predict favorable functional outcomes after inpatient stroke rehabilitation. This study provides health care professionals with evidence to evaluate predictors of favorable functional outcomes early at stroke rehabilitation, to tailor individualized interventions based on their client’s anticipated prognosis, and to educate clients about the benefits of making lifestyle changes to improve their anticipated rate of functional recovery.

Keywords: functional performance, predictors, stroke, recovery

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Akiode Ayobami, Akiode Akinsewa, Odeku Mojisola, Salako Busola, Odutolu Omobola, Nuhu Khadija

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Purpose: Evidence exists that family planning use can contribute to reduction in infant and maternal mortality in any country. Despite these benefits, contraceptive use in Nigeria still remains very low, only 10% among married women. Understanding factors that predict contraceptive use is very important in order to improve the situation. In this paper, we analysed data from the 2013 Nigerian Demographic and Health Survey (NDHS) to better understand predictors of contraceptive use in Nigeria. The use of logistics regression and other traditional models in this type of situation is not appropriate as they do not account for social structure influence brought about by the hierarchical nature of the data on response variable. We therefore used multilevel modelling to explore the determinants of contraceptive use in order to account for the significant variation in modern contraceptive use by socio-demographic, and other proximate variables across the different Nigerian states. Method: This data has a two-level hierarchical structure. We considered the data of 26, 403 married women of reproductive age at level 1 and nested them within the 36 states and the Federal Capital Territory, Abuja at level 2. We modelled use of modern contraceptive against demographic variables, being told about FP at health facility, heard of FP on TV, Magazine or radio, husband desire for more children nested within the state. Results: Our results showed that the independent variables in the model were significant predictors of modern contraceptive use. The estimated variance component for the null model, random intercept, and random slope models were significant (p=0.00), indicating that the variation in contraceptive use across the Nigerian states is significant, and needs to be accounted for in order to accurately determine the predictors of contraceptive use, hence the data is best fitted by the multilevel model. Only being told about family planning at the health facility and religion have a significant random effect, implying that their predictability of contraceptive use varies across the states. Conclusion and Recommendation: Results showed that providing FP information at the health facility and religion needs to be considered when programming to improve contraceptive use at the state levels.

Keywords: multilevel modelling, family planning, predictors, Nigeria

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Authors: Rosita Kanapeckaite

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Every year, some candidates who enroll in Generolas Jonas Zemaitis Military Academy of Lithuania do not complete a basic seven weeks cadet course and leave the Academy. Experience in other countries shows that psychological resilience grit and intrinsic motivation can lead to better course completion results. We examined the psychological resilience grit and intrinsic motivation as predictors of better results among newcomers who participate in the Cadet Basic Training (CBT) course. Based on past research and theory of other countries' military academies, we expected that resilience grit, and intrinsic motivation would predict performance in the Cadet Basic Training course. Results of regression analyses revealed that resilience and grit can predict better course results, but intrinsic motivation can not predict retention. These findings suggest that resilience and grit assessment and training may prove valuable in enhancing performance and retention within military training environments.

Keywords: military, intrinsic motivation, grit, resilience

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Authors: Selen Demirtas-Zorbaz

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This study aimed to determine if there is any relation between child–parent relationships and parental self-efficacy. The participants of this study are 208 parents, and 82,5% of them are mothers. The children’s age range are differed from 4 to 13 (x̄=7,8). The results showed that there is a significant positive correlation between positive relationship with parents and parental self-efficacy (r=0.52, p < .01); and significant negative correlation between conflict with parents and parental self-efficacy (r=-0.28, p < .01). Also, findings reveal that there was no significant correlation between the time spent with the child and conflict with parents (r=-0.08, p>.05). It was also found that there was no significant correlation between the time spends with the child and positive relationship with parents (r=0.08, p > 0.5). In addition to this; regression analysis’ results indicated that parental self-efficacy is significant predictors of conflict (β=-.268, t=-4.002, p < .001) and positive relationship with parents (β =.519, t= 8.733, p < .001) whereas time spent with children is not (β =-.070, t=-1,045, p > .05 for conflict; β =.061, t=1.023, p > .05 for positive relationship with parents).

Keywords: child-parent relationship, conflict with parents, positive relationship with parents, parental efficacy

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Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

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In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised functional principal component analysis method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: supervised, functional principal component analysis, functional response, functional linear regression

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

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Authors: Rukhsana Kausar, Nida Zafar

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The present research investigated socio-demographic predictors of divorce adjustment in Pakistani women. The sample comprised of 80 divorced women from different areas of Lahore. Self developed Socio-Demographic predictor scale and Divorce Adjustment Scale by (Fisher, 2001) was used for assessment. Analyses showed that working divorced women living with joint family system are more adjusted as compared to non-working divorced women living with joint family system. Women having one child are more adjusted as compared to women having more than one child. Findings highlight importance of presence of father for healthy development of adolescents. Adjustment of divorcee women was positively associated with income, social support from the family, having favorable attitudes toward marital dissolution prior to divorce, and being the partner who initiated the divorce. In addition, older women showed some evidence of poorer adjustment than did younger women. Findings highlight importance of support for divorce adjustment.

Keywords: socio-demographic, adjustment, women, divorce

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Authors: Dana El-Mughayyar, Neil Manson, Erin Bigney, Eden Richardson, Dean Tripp, Edward Abraham

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Use of narcotics to treat pain has increased over the past two decades and is a contributing factor to the current public health crisis. Understanding the pre-operative risks of chronic narcotic use may be aided through investigation of psychological measures. The objective of the reported study is to determine predictors of narcotic use two years post-surgery in a thoracolumbar spine surgery population, including an array of psychological factors. A prospective observational study of 191 consecutively enrolled adult patients having undergone thoracolumbar spine surgery is presented. Baseline measures of interest included the Pain Catastrophizing Scale (PCS), Tampa Scale for Kinesiophobia, Multidimensional Scale for Perceived Social Support (MSPSS), Chronic Pain Acceptance Questionnaire (CPAQ-8), Oswestry Disability Index (ODI), Numeric Rating Scales for back and leg pain (NRS-B/L), SF-12’s Mental Component Summary (MCS), narcotic use and demographic variables. The post-operative measure of interest is narcotic use at 2-year follow-up. Narcotic use is collapsed into binary categories of use and no use. Descriptive statistics are run. Chi Square analysis is used for categorical variables and an ANOVA for continuous variables. Significant variables are built into a hierarchical logistic regression to determine predictors of post-operative narcotic use. Significance is set at α < 0.05. Results: A total of 27.23% of the sample were using narcotics two years after surgery. The regression model included ODI, NRS-Leg, time with condition, chief complaint, pre-operative drug use, gender, MCS, PCS subscale helplessness, and CPAQ subscale pain willingness and was significant χ² (13, N=191)= 54.99; p = .000. The model accounted for 39.6% of the variance in narcotic use and correctly predicted in 79.7% of cases. Psychological variables accounted for 9.6% of the variance over and above the other predictors. Conclusions: Managing chronic narcotic usage is central to the patient’s overall health and quality of life. Psychological factors in the preoperative period are significant predictors of narcotic use 2 years post-operatively. The psychological variables are malleable, potentially allowing surgeons to direct their patients to preventative resources prior to surgery.

Keywords: narcotics, psychological factors, quality of life, spine surgery

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Authors: Ssekamanya, Mastura Badzis, Khamsiah Ismail, Dayang Shuzaidah Bt Abduludin

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With rising incidents of school violence worldwide, educators and researchers are trying to understand and find ways to enhance the safety of children at school. The purpose of this study was to investigate the extent to which the demographic variables of gender, age, length of service, position, academic qualification, and school location predicted teachers’ awareness about school safety practices in Malaysian primary schools. A stratified random sample of 380 teachers was selected in the central Malaysian states of Kuala Lumpur and Selangor. Multiple regression analysis revealed that none of the factors was a good predictor of awareness about school safety training, delivery methods of school safety information, and available school safety programs. Awareness about school safety activities was significantly predicted by school location (whether the school was located in a rural or urban area). While these results may reflect a general lack of awareness about school safety among primary school teachers in the selected locations, a national study needs to be conducted for the whole country.

Keywords: school safety awareness, predictors of school safety, multiple regression analysis, malaysian primary schools

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Authors: Bin Liu

Abstract:

As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

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Authors: Shu-Ching Chen, Li-Yun Lee

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The purpose of the study was to identify the factors associated with head and neck cancer-related lymphoedema (HNCRL)-related symptoms, body image, and HNCRL-related functional outcomes among patients with resected advanced head and neck cancer. A cross-sectional correlational design was conducted to examine the predictors of HNCRL-related functional outcomes in patients with resected advanced head and neck cancer. Eligible patients were recruited from a single medical center in northern Taiwan. Consecutive patients were approached and recruited from the Radiation Head and Neck Outpatient Department of this medical center. Eligible subjects were assessed for the Symptom Distress Scale–Modified for Head and Neck Cancer (SDS-mhnc), Brief International Classification of Functioning, Disability and Health (ICF) Core Set for Head and Neck Cancer (BCSQ-H&N), Body Image Scale–Modified (BIS-m), The MD Anderson Head and Neck Lymphedema Rating Scale (MDAHNLRS), The Foldi’s Stages of Lymphedema (Foldi’s Scale), Patterson’s Scale, UCLA Shoulder Rating Scale (UCLA SRS), and Karnofsky’s Performance Status Index (KPS). The results showed that the worst problems with body HNCRL functional outcomes. Patients’ HNCRL symptom distress and performance status are robust predictors across over for overall HNCRL functional outcomes, problems with body HNCRL functional outcomes, and activity and social functioning HNCRL functional outcomes. Based on the results of this period research program, we will develop a Cancer Rehabilitation and Lymphedema Care Program (CRLCP) to use in the care of patients with resected advanced head and neck cancer.

Keywords: head and neck cancer, resected, lymphedema, symptom, body image, functional outcome

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Authors: Muhammad Sulman, Tabinda Khurshid, Afsheen Masood

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The current research focused on determining the factors that determine the brand loyalty in consumers. It was hypothesized that there are certain demographical features that lead the consumers to adhere more towards certain brands. Cross-sectional research design was used. The sample for the current research comprised of participants (N=500) from age group 16 to 55 years. The data was collected through self-constructed demographic questionnaire as well as from a self-constructed Brand Loyalty Questionnaire. Brand Loyalty Questionnaire was adapted after taking permission from researchers. A pilot study was conducted to chalk out all the ambiguities of the questionnaire. The final version was administered on 250 participants. The descriptive and inferential analyses were carried on through SPSS version 24.00 to explore the factors that determine Brand Loyalty. The findings revealed that there is a relationship between brand loyalty and brand loyalty demographics and certain factors emerged as significant predictors of brand loyalty in young and middle aged consumers. The research findings carry strong implications for organizational and consumer psychologists in particular and for professionals in marketing and policy making in general.

Keywords: consumers, consumer psychologists, marketing, organizational, policy making

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Authors: Nai-Jiin Yang, Tyler Renshaw

Abstract:

Prior research has suggested that youth internalizing and externalizing problems significantly correlate with student subjective wellbeing (SSW) and achievement problems (SAP). Yet, only a few studies have used data from mental health screener based on the dual-factor model to explore the empirical relationships among internalizing problems, externalizing problems, academic problems, and student wellbeing. This study was conducted through a secondary analysis of previously collected data in school-wide mental health screening activities across secondary schools within a suburban school district in the western United States. The data set included 1880 student responses from a total of two schools. Findings suggest that both internalizing and externalizing problems are substantial predictors of both student wellbeing and academic problems. However, compared to internalizing problems, externalizing problems were a much stronger predictor of academic problems. Moreover, this study did not support academic problems that moderate the relationship between SSW and youth internalizing problems (YIP) and between youth externalizing problems (YEP) and SSW. Lastly, SAP is the strongest predictor of SSW than YIP and YEP.

Keywords: academic problems, externalizing problems, internalizing problems, school mental health, student wellbeing, universal mental health screening

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Authors: Bedilu A. Ejigu, Eshetu Wencheko, Kiros Berhane

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Anaemia is a condition in which the haemoglobin concentration falls below an established cut-off value due to a decrease in the number and size of red blood cells. The current study aimed to assess the spatial pattern and identify predictors related to anaemia using the third Ethiopian demographic health survey which was conducted in 2010. To achieve this objective, this study took into account the clustered nature of the data. As a result, multilevel modeling has been used in the statistical analysis. For analysis purpose, only complete cases from 15,909 females, and 13,903 males were considered. Among all subjects who agreed for haemoglobin test, 5.49 %males, and 19.86% females were anaemic. In both binary and ordinal outcome modeling approaches, educational level, age, wealth index, BMI and HIV status were identified to be significant predictors for anaemia prevalence. Furthermore, it was noted that pregnant women were more anaemic than non-pregnant women. As revealed by Moran's I test, significant spatial autocorrelation was noted across clusters. The risk of anaemia was found to vary across different regions, and higher prevalence was observed in Somali and Affar region.

Keywords: anaemia, Moran's I test, multilevel models, spatial pattern

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Authors: Teresa Wills, Geraldine Mccarthy, Nicola Cornally

Abstract:

Background: Obesity is an emerging healthcare epidemic affecting virtually all age and socio-economic groups and is one of the most serious and prevalent diseases of the 21st century. It is a public health challenge because of its prevalence, associated costs and health effects. The increasing prevalence of obesity has created a social perception that overweight body sizes are healthy and normal. This normalization of obesity within our society and the acceptance of higher body weights have led to individuals being unaware of the reality of their weight status and gravity of this situation thus impeding recognition of obesity. Given the escalating global health problem of obesity and its co-morbidities, the need to re-appraise its management is more compelling than ever. It is widely accepted that the causes of obesity are complex and multi-factorial. Engagement of individuals in weight management programmes is difficult if they do not perceive they have a problem with their weight. Recognition of the problem is a key component of obesity management and identifying the main predictors of behaviour is key to designing health behaviour interventions. Aim: The aim of the research was to determine factors relating to motivation to change behaviours in individuals who perceive themselves to be overweight. Method: The research design was quantitative, correlational and cross-sectional. The design was guided by the Health Belief Model. Data were collected online using a multi-section and multi-item questionnaire, developed from a review of the theoretical and empirical research. A sample of 202 men and women who perceived themselves to be overweight participated in the research. Descriptive and inferential statistical analyses were employed to describe relationships between variables. Findings: Following multivariate regression analysis, perceived barriers to weight loss and perceived benefits of weight loss were significant predictors of motivation to change behaviour. The perceived barriers to weight loss which were significant were psychological barriers to weight loss (p = < 0.019) and environmental barriers to physical activity (p= < 0.032).The greatest predictor of motivation to change behaviour was the perceived benefits of weight loss (p < 0.001). Perceived susceptibility to obesity and perceived severity of obesity did not emerge as significant predictors in this model. Total variance explained by the model was 33.5%. Conclusion: Perceived barriers to weight loss and perceived benefits of weight loss are important determinants of motivation to change behaviour. These findings have important implications for health professionals to help inform their practice and for the development of intervention programmes to prevent and control obesity.

Keywords: motivation to change behaviours, obesity, predictors of behavior, interventions, overweight

Procedia PDF Downloads 384