Relevant bibliographies by topics / Cross-sectional Regression

Academic literature on the topic 'Cross-sectional Regression'

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Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Cross-sectional Regression"

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Robinson, Peter M. "Nonparametric trending regression with cross-sectional dependence." Journal of Econometrics 169, no. 1 (July 2012): 4–14. http://dx.doi.org/10.1016/j.jeconom.2012.01.005.

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Liu, Jie, Zaixia Hu, and Shaohua Tan. "Cross-sectional stock return analysis using support vector regression." Applied Economics Letters 17, no. 1 (April 2, 2008): 71–74. http://dx.doi.org/10.1080/13504850701719777.

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Vanhonacker, Wilfried R., and Diana Day. "Cross-Sectional Estimation in Marketing: Direct Versus Reverse Regression." Marketing Science 6, no. 3 (August 1987): 254–67. http://dx.doi.org/10.1287/mksc.6.3.254.

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MARTUZZI, M., and P. ELLIOTT. "CROSS-SECTIONAL DATA ANALYSIS: A SIMPLE ALTERNATIVE TO LOGISTIC REGRESSION." Epidemiology 7, Supplement (July 1996): S70. http://dx.doi.org/10.1097/00001648-199607001-00207.

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Hodoshima, Jiro, Xavier Garza–Gómez, and Michio Kunimura. "Cross-sectional regression analysis of return and beta in Japan." Journal of Economics and Business 52, no. 6 (November 2000): 515–33. http://dx.doi.org/10.1016/s0148-6195(00)00031-x.

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Kirby, Chris. "Firm Characteristics, Cross-Sectional Regression Estimates, and Asset Pricing Tests." Review of Asset Pricing Studies 10, no. 2 (June 25, 2019): 290–334. http://dx.doi.org/10.1093/rapstu/raz005.

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Abstract I test a number of well-known asset pricing models using regression-based managed portfolios that capture nonlinearity in the cross-sectional relation between firm characteristics and expected stock returns. Although the average portfolio returns point to substantial nonlinearity in the data, none of the asset pricing models successfully explain the estimated nonlinear effects. Indeed, the estimated expected returns produced by the models display almost no variation across portfolios. Because the tests soundly reject every model considered, it is apparent that nonlinearity in the relation between firm characteristics and expected stock returns poses a formidable challenge to asset pricing theory. (JEL G12, C58)
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Wang, Na. "Association between Arsenic and Generalized Anxiety Disorder: A Cross-Sectional Study." Women Health Care and Issues 4, no. 4 (May 27, 2021): 01–05. http://dx.doi.org/10.31579/2642-9756/054.

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Aim: In some regions of Bayannaoer arsenic concentration in well drinking water is higher than the international standard of 10 μg/L. The purpose of this study is to evaluate the impact of exposures to arsenic in drinking water on generalized anxiety disorder (GAD). Materials and Methods: A survey was conducted in 2016 among villagers in Hangjinhou County, Bayannaoer City, Inner Mongolia. A questionnaire was used to inquire about GAD, arsenic related neurological symptoms. Arsenic concentration in the water was measured and arsenicosis prevalence was assessed. Multinomial logistic regression and ordinal logistic regression were performed to evaluate the association of abnormal arsenic levels on increased GAD symptoms. Results: 446 participants were enrolled. Subjects with exposure to water arsenic levels>10 μg/L were significantly more likely to have mild GAD than controls (adjusted odds ratio [AOR] =2.3, 95% confidence interval [CI], 1.1-4.8). Participants who were diagnosed with arsenicosis were more likely to report mild anxiety than minimal anxiety compared to those who did not (AOR=2.3, 95% CI, 1.3-4.1). Survey respondents with palpitations, forgetfulness, headaches, dizziness, decreased taste, decreased hearing, loss of touch, abnormal warm and cold sensation, blurred vision, numbness and tingling were more likely to report mild, moderate and severe anxiety. Conclusions: Arsenic exposure was associated with a higher risk of GAD. Screening for arsenic exposure should be incorporated into the evaluation of GAD, in areas where arsenic in drinking water is known to be abnormal.
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KAN, RAYMOND, CESARE ROBOTTI, and JAY SHANKEN. "Pricing Model Performance and the Two-Pass Cross-Sectional Regression Methodology." Journal of Finance 68, no. 6 (November 12, 2013): 2617–49. http://dx.doi.org/10.1111/jofi.12035.

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Hur, Jungshik, Raman Kumar, and Vivek Singh. "Cross-sectional regression of returns on betas and portfolio grouping procedures." International Journal of Business and Systems Research 8, no. 1 (2014): 1. http://dx.doi.org/10.1504/ijbsr.2014.058005.

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Karafiath, Imre. "Estimating cross-sectional regressions in event studies with conditional heteroskedasticity and regression designs that have leverage." International Journal of Managerial Finance 10, no. 4 (August 26, 2014): 418–31. http://dx.doi.org/10.1108/ijmf-12-2012-0134.

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Purpose – In the finance literature, fitting a cross-sectional regression with (estimated) abnormal returns as the dependent variable and firm-specific variables (e.g. financial ratios) as independent variables has become de rigueur for a publishable event study. In the absence of skewness and/or kurtosis the explanatory variable, the regression design does not exhibit leverage – an issue that has been addressed in the econometrics literature on the finite sample properties of heteroskedastic-consistent (HC) standard errors, but not in the finance literature on event studies. The paper aims to discuss this issue. Design/methodology/approach – In this paper, simulations are designed to evaluate the potential bias in the standard error of the regression coefficient when the regression design includes “points of high leverage” (Chesher and Jewitt, 1987) and heteroskedasticity. The empirical distributions of test statistics are tabulated from ordinary least squares, weighted least squares, and HC standard errors. Findings – None of the test statistics examined in these simulations are uniformly robust with regard to conditional heteroskedasticity when the regression includes “points of high leverage.” In some cases the bias can be quite large: an empirical rejection rate as high as 25 percent for a 5 percent nominal significance level. Further, the bias in OLS HC standard errors may be attenuated but not fully corrected with a “wild bootstrap.” Research limitations/implications – If the researcher suspects an event-induced increase in return variances, tests for conditional heteroskedasticity should be conducted and the regressor matrix should be evaluated for observations that exhibit a high degree of leverage. Originality/value – This paper is a modest step toward filling a gap on the finite sample properties of HC standard errors in the event methodology literature.
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Dissertations / Theses on the topic "Cross-sectional Regression"

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Hargarten, Paul. "A Cross-Sectional Analysis of Health Impacts of Inorganic Arsenic in Chemical Mixtures." VCU Scholars Compass, 2015. http://scholarscompass.vcu.edu/etd/3788.

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Drinking groundwater is the primary way humans accumulate arsenic. Chronic exposure to inorganic arsenic (iAs) (over decades) has been shown to be associated with multiple health effects at low levels (5-10 ppb) including: cancer, elevated blood pressure and cardiovascular disease, skin lesions, renal failure, and peripheral neuropathy. Using hypertension (or high blood pressure) as a surrogate marker for cardiovascular disease, we examined the effect of iAs alone and in a mixture with other metals using a cross-sectional study of adults in United States (National Health and Examination Survey, NHANES, 2005-2010) adjusting for covariates: urinary creatinine level (mg/dL), poverty index ratio (PIR, measure of socioeconomic status, 1 to 5), age, smoking (yes/no), alcohol usage, gender, non-Hispanic Black, and overweight (BMI>=25). A logistic regression model suggests that a one-unit increase in log of inorganic arsenic increases the odds of hypertension by a factor of 1.093 (95% Confidence Interval=0.935, 1.277) adjusted for these covariates , which indicates that there was not significant evidence to claim that inorganic arsenic is a risk factor for hypertension. Biomonitoring data provides evidence that humans are not only exposed to inorganic arsenic but also to mixtures of chemicals including inorganic arsenic, total mercury, cadmium, and lead. We tested for a mixture effect of these four environmental chemicals using weighted quantile sum (WQS) regression, which takes into account the correlation among the chemicals and with the outcome. For one-unit increase in the weighted sum, the adjusted odds of developing hypertension increases by a factor of 1.027 (95% CI=0.882,1.196), which is also not significant after taking into account the same covariates. The insignificant finding may be due to the low inorganic arsenic concentration (8-620 μg /L) in US drinking water, compared to those in countries like Bangladesh where the concentrations are much higher. Literature provides conflicting evidence of the association of inorganic arsenic and hypertension in low/moderate regions; future studies, especially a large cohort study, are needed to confirm if inorganic arsenic alone or with other metals is associated with hypertension in the United States.
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Yu, Mingyu Carleton University Dissertation Mathematics. "Nested-error regression models and small area estimation combining cross-sectional and time series data." Ottawa, 1993.

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NOVAES, ANDRE LUIZ FARIAS. "ECONOMETRIC GENETIC PROGRAMMING: A NEW APPROACH FOR REGRESSION AND CLASSIFICATION PROBLEMS IN CROSS-SECTIONAL DATASETS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=25338@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Esta dissertação propõe modelos parcimoniosos para tarefas de regressão e classificação em conjuntos de dados exclusivamente seccionais, mantendo-se a hipótese de amostragem aleatória. Os modelos de regressão são lineares, estimados por Mínimos Quadrados Ordinários resolvidos pela Decomposição QR, apresentando solução única sob posto cheio ou não da matriz de regressores. Os modelos de classificação são não lineares, estimados por Máxima Verossimilhança utilizando uma variante do Método de Newton, nem sempre apresentando solução única. A parcimônia dos modelos de regressão é fundamentada na prova matemática de que somente agregará acurácia ao modelo o regressor que apresentar módulo da estatística de teste, em um teste de hipótese bicaudal, superior à unidade. A parcimônia dos modelos de classificação é fundamentada em significância estatística e embasada intuitivamente no resultado teórico da existência de classificadores perfeitos. A Programação Genética (PG) realiza o processo de evolução de modelos, explorando o espaço de busca de possíveis modelos, constituídos de distintos regressores. Os resultados obtidos via Programação Genética Econométrica (PGE) – nome dado ao algoritmo gerador de modelos – foram comparados aos proporcionados por benchmarks em oito distintos conjuntos de dados, mostrando-se competitivos em termos de acurácia na maior parte dos casos. Tanto sob o domínio da PG quanto sob o domínio da econometria, a PGE mostrou benefícios, como o auxílio na identificação de introns, o combate ao bloat por significância estatística e a geração de modelos econométricos de elevada acurácia, entre outros.
This dissertation proposes parsimonious models for regression and classification tasks in cross-sectional datasets under random sample hypothesis. Regression models are linear in parameters, estimated by Ordinary Least Squares solved by QR Decomposition, presenting a unique solution under full rank of the regressor matrix or not. Classification models are nonlinear in parameters, estimated by Maximum Likelihood, not always presenting a unique solution. Parsimony in regression models is based on the mathematical proof that accuracy will be added to models only by the regressor that presents a test statistic module higher than a predefined value in a two-sided hypothesis test. Parsimony in classification models is based on statistical significance and, intuitively, on the theoretical result about the existence of perfect classifiers. Genetic Programming performs the evolution process of models, being responsible for exploring the search space of possible regressors and models. The results obtained with Econometric Genetic Programming – name of the algorithm in this dissertation – was compared with those from benchmarks in eight distinct cross-sectional datasets, showing competitive results in terms of accuracy in most cases. Both in the field of Genetic Programming and in that of econometrics, Econometric Genetic Programming has shown benefits such as help on introns identification, combat to bloat by statistical significance and generation of high level accuracy models, among others.
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collet, CLAIRE, and Kimberlay Duquennoy. "Did the pattern of poverty in West Germany change because of the reunification? : A cross-sectional study of poverty in West Germany." Thesis, Linnéuniversitetet, Institutionen för nationalekonomi och statistik (NS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-85939.

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The reunification of West Germany and East Germany occurred in 1990 and had a great impact on the country. This essay investigates the impact that reunification had on the poverty structure of West Germany on the long-run. The results indicate that reunification had a negative impact on poverty since it increased the poverty rate by 4.88 percentage point in 2000 and by 6.16 percentage point in 2005. The structure of the poor population slightly changed the year following the reunification. Five years later, the structure of the poor population was similar to what it was before the reunification. However, during this period, the income transfer became more efficient since it decreased poverty by 6 percentage point to 16 percentage point more after reunification than it used to do before.
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Klekamp, Benjamin Glenn. "Assessing the Relationship of Monocytes with Primary and Secondary Dengue Infection among Hospitalized Dengue Patients in Malaysia, 2010: A Cross-Sectional Study." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3185.

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Dengue, a group of four similar viruses transmitted through the bite of a mosquito, is estimated to infect upwards of 100 million annually in over 100 nations throughout the global equatorial belt. Distribution of global dengue is highly skewed as Southeast Asian and Western Pacific regions endure 75% of the global dengue burden. Similar to other regional countries, Malaysia has been rapidly urbanizing, which has supported a hyperendemic dengue state. The biological pathway by which dengue infection causes a wide range of clinical manifestations, spanning asymptomatic to life-threatening severe complications, is not comprehensively understood. Historically, severe dengue complications have primarily occurred in children. Consequentially, the majority of the dengue biological pathway research has been conducted on children; however, extrapolation of research findings to adults may be inappropriate as dengue manifestations have differed between age groups. As developing countries undergo epidemiologic transitions and dengue continues to spread geographically to non-endemic regions, youth and adult populations have been subjected to more of the severe dengue burden. Epidemiology and laboratory-based evidence has supported both memory T-cell and antibody independent enhancement hypotheses to explain the biological pathway of severe dengue. Both hypotheses employ the central idea that a primary infection alters immune components so that during a secondary heterotypic dengue infection, an individual is more at risk for severe complications. Monocytes, immune cells that are pivotal in both hypotheses, have been highly examined through in vivo and in vitro experimentation; however, epidemiological evidence for monocyte involvement is incomplete. The primary objective of the study was to examine if a difference in absolute monocyte count, considering independent risk factors, is present in individuals with primary and secondary dengue infections. A secondary dengue infection was found to raise absolute monocyte count during the defervescence phase of dengue illness in individuals aged 15 years and older 0.71 ± 0.15 (x10^9) compared to those experiencing primary dengue infection. Gender and distance of study participants' residences from Hospital Ampang were found to be risk factors for the relationship of interest; whereas, age and race were not found to be significant risk factors. The study helps expand current knowledge of the severe dengue biological pathway with respect to immunological differences between primary and secondary dengue infections. Further research is needed to confirm and expand the findings of this initial study, specifically to include infecting dengue serotype, education, and socioeconomic status which are known dengue risk factors.
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Wang, Yue Nan, and wangyn14@hotmail com. "The diversification benefits and the risk and return relationships in the Chinese A-share market." RMIT University. Economics, Finance and Marketing, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20061205.103325.

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China's rapid economic growth and the development of its domestic stock market have attracted considerable attention from foreign investors. China's economic financial expansion, however, has emerged from an environment of state planning and radical socialist ideology. With a view of providing investors with a better understanding of the risk and return relationship in the Chinese A-share market over the past decade, this thesis adapts several empirical models to the circumstances in China and conducts four empirical analyses. First, in order to rationalize foreign investors' entry into the A-share market, the thesis compares the diversification benefits in three China-related stock markets, namely the A-share, the B-share and the H-share markets in a mean-variance framework using daily, weekly and monthly data respectively. The results suggest that of the three stock markets, the B-share market generates the highest average annual returns while the A-share market has the most significant diversification benefits regardless of whether the analysis is undertaken implementing a traditional mean-variance framework or a downside risk framework. Next, an empirical analysis using the Fama and MacBeth two-pass procedure is undertaken to test the relationship between beta, firm factors and stock returns. Similar to the findings in other stock markets, the results of this analysis show that the static betas for individual stocks fail to capture variation in stock returns in the A-share market. In contrast, the effects of book-to-market and trading volume are significant in the sample period. However, the fact that none of these factors have a persistent role in explaining stock returns suggests a possible change in the investment philosophy of Chinese domestic investors over the past decade. In the third analysis, two global betas are incorporated into the cross-sectional regressions in a bid to examine the integration or segmentation of the A-share market with the world and Hong Kong stock markets. Specifically, both time-varying betas and static betas are used in the analysis. The results suggest that there is no beta effect and the A-share marke t is totally segmented from both the world and Hong Kong stock markets. Finally, when the segmentation and integration status of the A-share market is further examined using the Maximum Likelihood Estimation framework without beta estimation and the assumption of a linear relationship between beta and stock returns, the findings suggest that the A-share market is becoming increasing integrated with the B-share and the Hong Kong stock markets.
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Wang, Yuenan, and yangyn14@hotmail com. "The diversification benefits and the risk and return relationships in the Chinese A-share market." RMIT University. Economics, Finance and Marketing, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080103.093949.

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China's rapid economic growth and the development of its domestic stock market have attracted considerable attention from foreign investors. China's economic financial expansion, however, has emerged from an environment of state planning and radical socialist ideology. With a view of providing investors with a better understanding of the risk and return relationship in the Chinese A-share market over the past decade, this thesis adapts several empirical models to the circumstances in China and conducts four empirical analyses. First, in order to rationalize foreign investors' entry into the A-share market, the thesis compares the diversification benefits in three China-related stock markets, namely the A-share, the B-share and the H-share markets in a mean-variance framework using daily, weekly and monthly data respectively. The results suggest that of the three stock markets, the B-share market generates the highest average annual returns while the A-share market has the most significant diversification benefits regardless of whether the analysis is undertaken implementing a traditional mean-variance framework or a downside risk framework. Next, an empirical analysis using the Fama and MacBeth two-pass procedure is undertaken to test the relationship between beta, firm factors and stock returns. Similar to the findings in other stock markets, the results of this analysis show that the static betas for individual stocks fail to capture variation in stock returns in the A-share market. In contrast, the effects of book-to-market and trading volume are significant in the sample period. However, the fact that none of these factors have a persistent role in explaining stock returns suggests a possible change in the investment philosophy of Chinese domestic investors over the past decade. In the third analysis, two global betas are incorporated into the cross-sectional regressions in a bid to examine the integration or segmentation of the A-share market with the world and Hong Kong stock markets. Specifically, both time-varying betas and static betas are used in the analysis. The results suggest that there is no beta effect and the A-share marke t is totally segmented from both the world and Hong Kong stock markets. Finally, when the segmentation and integration status of the A-share market is further examined using the Maximum Likelihood Estimation framework without beta estimation and the assumption of a linear relationship between beta and stock returns, the findings suggest that the A-share market is becoming increasing integrated with the B-share and the Hong Kong stock markets.
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Gashi, Arben, and Florent Sinani. "Adolescents, Sleep Deprivation and Externalizing Behaviour - Is There a Connection?" Thesis, Örebro universitet, Institutionen för juridik, psykologi och socialt arbete, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-65584.

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Rogers, Paul B. "An analysis of parameters of the U.S. pilot population from 1983-2005 from a scientific information system point of view : a foundation for computational epidemiological studies /." Oklahoma City : [s.n.], 2007.

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Keunecke, Johann Georg [Verfasser], Johannes [Akademischer Betreuer] Prottengeier, Johannes [Gutachter] Prottengeier, and Torsten [Gutachter] Birkholz. "Workload and influencing factors in non-emergency medical transfers: a multiple linear regression analysis of a cross-sectional questionnaire study / Johann Georg Keunecke ; Gutachter: Johannes Prottengeier, Torsten Birkholz ; Betreuer: Johannes Prottengeier." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2020. http://d-nb.info/1220506036/34.

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Books on the topic "Cross-sectional Regression"

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Uribe, Jorge M., and Montserrat Guillen. Quantile Regression for Cross-Sectional and Time Series Data. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1.

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Bulkley, George. Excessive stock price dispersion: A regression test of cross-sectional volatility. London: London School of Economics, Financial Markets Group, 1996.

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Kan, Raymond. Pricing model performance and the two-pass cross-sectional regression methodology. Cambridge, MA: National Bureau of Economic Research, 2009.

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Swaine, Daniel G. What do cross-sectional growth regressions tell us about convergence? [Boston]: Federal Reserve Bank of Boston, 1998.

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Swaine, Daniel G. What do cross-sectional growth regressions tell us about convergence? [Boston]: Federal Reserve Bank of Boston, 1998.

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Swaine, Daniel G. What do cross-sectional growth regressions tell us about convergence? [Boston]: Federal Reserve Bank of Boston, 1998.

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Uribe, Jorge M., and Montserrat Guillen. Quantile Regression for Cross-Sectional and Time Series Data: Applications in Energy Markets Using R. Springer, 2020.

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Lee, Patricia, Donald Stewart, and Stephen Clift. Group Singing and Quality of Life. Edited by Brydie-Leigh Bartleet and Lee Higgins. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190219505.013.22.

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International research has broadly reported positive effects of singing on health. Choral singing, a social activity, can contribute to health and social and emotional well-being through enhancing individual and social variables, such as a sense of motivation, personal worth, concentration, and social engagement. This cross-sectional study aimed to establish a quantitative model to explain how multiple attributes of choral singing interact to impact on different dimensions of health and well-being. Using data from an Australian subsample within a multinational project, the results, from a series of stepwise hierarchical regression models, showed that choral singing benefited the choir members’ physical and psychological health and well-being through social engagement and a sense of positive identity. Choral singing also impacted social health and well-being positively by promoting feelings of excitement and importance to life, as well as longer duration of involvement in the choir. This study will contribute to developing targeted group singing or social activities to promote continued physical, psychological, and social health.
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Li, Quan. Using R for Data Analysis in Social Sciences. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190656218.001.0001.

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This book seeks to teach undergraduate and graduate students in social sciences how to use R to manage, visualize, and analyze data in order to answer substantive questions and replicate published findings. This book distinguishes itself from other introductory R or statistics books in three ways. First, targeting an audience rarely exposed to statistical programming, it adopts a minimalist approach and covers only the most important functions and skills in R that one will need for conducting reproducible research projects. Second, it emphasizes meeting the practical needs of students using R in research projects. Specifically, it teaches students how to import, inspect, and manage data; understand the logic of statistical inference; visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots; and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. Third, it teaches students how to replicate the findings in published journal articles and diagnose model assumption violations. The principle behind this book is to teach students to learn as little R as possible but to do as much reproducible, substance-driven data analysis at the beginner or intermediate level as possible. The minimalist approach dramatically reduces the learning cost but still proves adequate information for meeting the practical research needs of senior undergraduate and beginning graduate students. Having completed this book, students can use R and statistical analysis to answer questions regarding some substantively interesting continuous outcome variable in a cross-sectional design.
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Egger, Eva-Maria, Cecilia Poggi, and Héctor Rufrancos. Welfare and the depth of informality: Evidence from five African countries. 25th ed. UNU-WIDER, 2021. http://dx.doi.org/10.35188/unu-wider/2021/963-1.

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This study explores the relationship between household poverty and depth of informality by proposing a new measure of informality at the household level. It is defined as the share of activities (hours worked or income earned) without social insurance for wage workers in the household. We apply cross-sectional regressions to five urban sub-Saharan African countries, showing that a household head informality dummy obscures a non-linear relationship between the depth of household informality and welfare outcomes. In some countries, a small share of income from formal jobs is associated with at least the same welfare as a fully formal portfolio. By assessing transitions between household portfolios with panel data for urban Nigeria, we also show that most welfare differences are explained by selection and that movements in and out of formality cannot sufficiently change welfare trajectories. The results call for better inclusion of informal profiles to social insurance programmes.
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Book chapters on the topic "Cross-sectional Regression"

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Uribe, Jorge M., and Montserrat Guillen. "Cross-sectional Quantile Regression." In Quantile Regression for Cross-Sectional and Time Series Data, 21–32. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_4.

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Uribe, Jorge M., and Montserrat Guillen. "Time Series Quantile Regression." In Quantile Regression for Cross-Sectional and Time Series Data, 33–44. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_5.

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Uribe, Jorge M., and Montserrat Guillen. "Quantile Regression: A Methodological Overview." In Quantile Regression for Cross-Sectional and Time Series Data, 13–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_3.

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Uribe, Jorge M., and Montserrat Guillen. "Novel Approaches in Quantile Regression." In Quantile Regression for Cross-Sectional and Time Series Data, 49–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_7.

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Uribe, Jorge M., and Montserrat Guillen. "Goodness of Fit in Quantile Regression Models." In Quantile Regression for Cross-Sectional and Time Series Data, 45–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_6.

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Uribe, Jorge M., and Montserrat Guillen. "Why and When Should Quantile Regression Be Used?" In Quantile Regression for Cross-Sectional and Time Series Data, 1–5. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_1.

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Uribe, Jorge M., and Montserrat Guillen. "A Case Study: Modeling Energy Markets by the Means of Quantile Regression." In Quantile Regression for Cross-Sectional and Time Series Data, 7–11. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_2.

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Uribe, Jorge M., and Montserrat Guillen. "What Have We Learned from Quantile Regression? Implications for Economics and Finance." In Quantile Regression for Cross-Sectional and Time Series Data, 55. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44504-1_8.

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Sutradhar, Brajendra C. "Overview of Regression Models for Cross-Sectional Univariate Categorical Data." In Springer Series in Statistics, 7–87. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-2137-9_2.

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Tian, Cunzhi, Qiuping Guo, and Haijun Wang. "The Performance Persistence of Mutual Fund: The Empirical Research Based on Cross-Sectional Regression." In Informatics in Control, Automation and Robotics, 193–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25899-2_26.

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Conference papers on the topic "Cross-sectional Regression"

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Jianbao, Chen, Cheng Tingting, and Wang Dengling. "Notice of Retraction: Quantile Regression Analysis of Cross Sectional Price-Volume Relation in Chinese Stock Markets." In 2009 International Forum on Information Technology and Applications (IFITA). IEEE, 2009. http://dx.doi.org/10.1109/ifita.2009.315.

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Ashour, Reem, Sana Elashie, Bayan Alkeilan, and Mujahed Shraim. "Smartphone Addiction among Qatar University Students: A Cross-Sectional study." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0203.

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Aims: The aim of this study was to: (I) estimate the prevalence of SPA among students in Qatar University (QU); (II) assess the correlation between daily duration of smartphone use (SPU) and SPA; (III) assess the relationship between SPA with (a) current Grade point Average (GPA), (b) psychological distress, and (c) students’ perceived negative impact of SPU on their learning and academic performance, sleep at night, social activity, and physical and mental health. Methods: We used a cross-sectional study using a selfadministered survey to address the aims of the study. An electronic survey was distributed to all QU students registered in the Fall 2019 in addition to a paper survey distribution to fifteen classes, selected at random from all colleges in QU. The survey used smartphone addiction scale (SAS) to measure SPA; General Health Questionnaire 28 (GHQ-28) to measure the likelihood of student having “psychological distress”; ten statements to identify students perceived negative impact of SPU on academic performance, sleep at night, physical and mental health, and social activity; current GPA as a measure of academic performance. Descriptive statistics and multivariable linear and logistics regression analyses were performed to analyses the data. The Study was ethically approved QU institutional review Board. Results: A total of 717 students participated in the study. The mean daily duration of SPU among students was 6.5 hours per day (SD= 3.7), and he prevalence of SPA was 59%. Duration of SPU in hours and SPA score (r=0.282, p= <0.001). The prevalence of psychological distress among students was 51.0%. Increase in daily duration of SPU, male gender, presence of psychological stress, not having a chronic disease, and not performing physical exercise in the previous week were independently associated with increased odds of SPA. We found a significant interaction between gender and psychological distress with SPA. Male students with psychological distress were at lower odds of SPA than female students with psychological distress (OR= 0.39; 95% CI 0.17, 0.87). SPA was a statistically significant predictor of all included domains of perceived negative impact of SPU, including sleep at night, learning in class, study time, academic performance, physical and mental health, and social activity. After adjustment for significant variables, students with no SPA had increased odds of having higher current GPA category by 2.04 times (1.05, 3.95) than students with SPA. The characteristics of students did not vary significantly according to survey completion method. The sensitivity analyses showed similar findings between the predictors and the outcome variables in all analyses. Therefore, our sensitivity analyses suggest that our findings are unlikely to have been affected by selection bias, response bias, or social acceptability bias. Conclusion: SPA is highly prevalent among QU students. SPA or longer duration of SPU have negative impact on academic performance, psychological distress, and perceived physical and mental health, and social activity.
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Hardiawan, Donny, Arief Anshory Yusuf, and Bagdja Muljarijadi. "THE IMPACT OF EXPENDITURE INEQUALITY AND SOCIOECONOMIC ON CRIME RATES IN INDONESIA. CROSS SECTIONAL STUDY USING SPATIAL ECONOMETRICS AND GEOGRAPHICALLY WEIGHTED REGRESSION." In Proceedings of the Achieving and Sustaining SDGs 2018 Conference: Harnessing the Power of Frontier Technology to Achieve the Sustainable Development Goals (ASSDG 2018). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/assdg-18.2019.14.

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D. Guillén-Gámez, Francisco. "A cross-sectional study on attitudes towards statistics in primary education students of Higher Education: prediction of variables through a multiple regression model." In 2nd International Conference on Modern Research in Education, Teaching and Learning. Acavent, 2020. http://dx.doi.org/10.33422/2nd.icmetl.2020.11.82.

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Hallingberg, B., O. Maynard, L. Gray, A. MacKintosh, E. Lowthian, and G. Moore. "OP59 #Have e-cigarettes re-normalized or displaced youth smoking?: a segmented regression analysis of repeated cross sectional survey data in england, scotland and wales." In Society for Social Medicine 62nd Annual Scientific Meeting, Hosted by the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, 5–7 September 2018. BMJ Publishing Group Ltd, 2018. http://dx.doi.org/10.1136/jech-2018-ssmabstracts.58.

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‘Arub, Lathifah, Eti Poncorini Pamungkasari, and Yulia Lanti Retno Dewi. "Multiple Logistic Regression on the Factors Affecting Exclusive Breastfeeding Practice in Karanganyar, Central Java." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.03.89.

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ABSTRACT Background: Breastfeeding peer support helps lactating women to sustain breastfed and reduce cultural barriers. This study aimed to examine the effects of maternal age, maternal education, maternal employment, type of labor, knowledge, attitude, family support, and social capital on breastfeeding practice. Subjects and Method: A cross sectional study was conducted at 25 integrated health posts in Karanganyar, Central Java, from August to September 2019. A sample of 200 lactating mothers with children aged 7-12 months was selected by stratified random sampling. The dependent variable was exclusive breastfeeding. The independent variables were maternal age, maternal education, maternal employment, type of labor, knowledge, attitude, family support, and social capital. The data were collected by questionnaire and analyzed by a multipe logistic regression. Results: Exclusive breastfeeding increased with maternal age 20-34 years (b= 1.96; 95% CI= 0.53 to 3.39; p= 0.007), maternal education ≥Senior high school (b= 1.47; 95% CI= 0.08 to 2.87; p= 0.038), good knowledge (b= 1.73; 95% CI= 0.33 to 3.12; p= 0.015), positive attitude (b= 1.61; 95% CI= 0.28 to 2.94; p= 0.017), strong family support (b= 1.39; 95% CI= 0.13 to 2.65; p= 0.030), and strong social capital (b= 1.34; 95% CI= 0.01 to 2.68; p= 0.049). Exclusive breastfeeding decreased with mothers working outside the house (b= -2.95; 95% CI= -4.37 to -1.53; p<0.001) and sectio cesarean labor (b= -1.57; 95% CI= -3.06 to -0.08; p= 0.039). Conclusion: Exclusive breastfeeding increases with maternal age 20-34 years, maternal education ≥Senior high school, good knowledge, positive attitude, strong family support, and strong social capital. Exclusive breastfeeding decreases with mothers working outside the house and sectio cesarean labor. Keywords: exclusive breastfeeding, bipsychosocial Correspondence: Lathifah ‘Arub. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java, Indonesia. Email: lathifah.arub17@gmail.com. Mobile: +625789212539. DOI: https://doi.org/10.26911/the7thicph.03.89
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Zamzam, Maki, Didik Gunawan Tamtomo, and Vitri Widyaningsih. "Biopsychosocial Determinants of Quality of Life in Post Stroke Patients: A Multiple Logistic Regression Analysis." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.01.35.

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ABSTRACT Background: The impact of stroke on health may be disastrous. Stroke can affect multiple domains of quality of life. The purpose of this study was to examine biopsychosocial determinants of quality of life in post stroke patients. Subjects and Method: A cross sectional study was conducted at Surakarta hospital, Central Java, from September to October 2019. A sample of 200 post stroke patients was selected for this study purposively. The dependent variable was quality of life. The independent variables were age, gender, empoyment, income, family income, marital status, history of stroke attack, co-morbidity, duration of illness, functional disorder, depression, and family support. The data were collected by medical record and questionnaire. The data were analyzed by a multiple logistic regression. Results: Quality of life of post stroke patients increased with married (b= 1.79; 95% CI= 0.24 to 3.35; p= 0.024), employed (b= 1.93; 95% CI= 0.13 to 3.72; p= 0.035), mild fuctional disorder (b=1.68; 95% CI= 0.11 to 3.25; p= 0.036), and strong family support (b= 2.17; 95% CI= 0.46 to 3.88; p= 0.013). Quality of life of post stroke patients decreased with age ≥60 years (b= -1.99; 95% CI= -3.80 to -0.17; p= 0.032), female (b= -1.74; 95% CI= -3.28 to -0.19; p= 0.027), stroke attack >1 time (b= -1.87; 95% CI= -3.59 to -0.15; p= 0.033), length of illness ≥6 months (b= -2.12; 95% CI= -3.87 to -0.36; p= 0.018), co-morbidity (b= -1.96; 95% CI= -3.67 to -0.24; p= 0.025), and depression (b= -1.40; 95% CI= -2.97 to 0.16; p= 0.078). Conclusion: Quality of life of post stroke patients increases with married, employed, mild fuctional disorder, and strong family support. Quality of life of post stroke patients decreases with age ≥60 years, female, stroke attack >1 time, length of illness ≥6 months, co-morbidity, and depression. Keywords: stroke, quality of life, depression, functional disorder Correspondence: Maki Zamzam. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java, Indonesia. Email: makizz477@gmail.com. Mobile: +6281251543935 DOI: https://doi.org/10.26911/the7thicph.01.35
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Martaningrum, Herlina Ika, Uki Retno Budihastuti, and Bhisma Murti. "Factors Affecting the Use of Visual Inspection Acetic Acid Test in Magelang, Central Java." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.03.90.

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ABSTRACT Background: Visual inspection acetic acid (VIA) can help detect cervical cancer at an early stage. However, under-utilization of the screening (e.g. rural residence, poor knowledge, low education, acceptability by the healthcare providers, etc.) persists as a major challenge. This study aimed to determine factors affecting the use of VIA test. Subjects and Method: A cross sectional study was carried out at 25 community health centers (puskesmas) in Magelang, Central Java, from September to October 2019. A sample of 200 women aged 30-50 years old was selected for this study randomly. The dependent variable was VIA test. The independent variables were knowledge, observational learning, reinforcement, cues to action, informational access, attitude, self-efficacy, outcome expectation, and family support. The data were collected by questionnaire and analyzed by a multiple logistic regression. Jenis penelitian ini adalah analitik observasional dengan pendekatan cross sectional. Results: VIA use increased with good knowledge (b= 3.97; 95% CI= 0.84 to 7.10; p= 0.013), high observational learning (b= 2.20; 95% CI= -0.09 to 4.49; p= 0.060), srong reinforcement behavior (b= 3.90; 95% CI= 1.02 to 6.77; p= 0.008), strong cues to action (b= 4.87; 95% CI= 1.07 to 8.67; p= 0.012), good information access (b= 3.32; 95% CI= 0.94 to 5.69; p= 0.006), strong family support (b= 3.81; 95% CI= 0.62 to 6.99; p= 0.019), positive attitude (b= 2.91; 95% CI= 0.20 to 5.62; p= 0.035), strong self efficacy (b= 2.71; 95% CI= 0.44 to 4.99; p= 0.019), and high outcome expectation (b= 3.22; 95% CI= 0.72 to 5.73; p= 0.012). Conclusion: VIA use increases with good knowledge, high observational learning, srong reinforcement behavior, strong cues to action, good information access, strong family support, positive attitude, strong self efficacy, and high outcome expectation. Keywords: cervical cancer, visual inspection acetic acid, social cognitive theory Correspondence: Herlina Ika Martaningrum. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta, Central Java, Indonesia. Email: herlinaika21@gmail.com. Mobile: 085643528156 DOI: https://doi.org/10.26911/the7thicph.03.90
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Pangesti, Tri Puji, Didik Gunawan Tamtomo, and Bhisma Murti. "Multilevel Logistic Regression Analysis on the Effectiveness of Chronic Disease Management Program in Improving “Cerdik” Healthy Behavior for Hypertensive Patients." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.04.44.

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ABSTRACT Background: The chronic disease management program (prolanis) was established in Indonesia to help people achieve optimal quality of life with cost-effective and efficient health services. The user targets were national health insurance participants who suffer from chronic disease, including hypertension and diabetes mellitus. This study aimed to examine the effectiveness of prolanis in improving “CERDIK” healthy behavior for hypertensive patients. Subjects and Method: A cross sectional study was carried out at 25 community health centers in Gunungkidul, Yogyakarta, Indonesia, from January to February 2020. A sample of 200 hypertensive patients were selected by stratified random sampling. The dependent variable was healthy behavior. The independent variables were sex, education, family support, peer support, and prolanis. The data were collected by questionnaire and analyzed by a multiple logistic regression run on Stata 13. Results: Healthy behavior in patients with hypertension increased with (b= 1.95; 95% CI= 0.76 to 3.16; p= 0.001), participative in prolanis (b= 3.93; 95% CI= 2.42 to 5.44; p<0.001), strong family support (b= 1.38; 95% CI= 0.09 to 2.67; p= 0.035), strong peer support (b= 0.50; 95% CI= -0.81 to 1.91; p= 0.427), and female (b= 0.89; 95% CI= -0.35 to 2.13; p=0.160). Community health center had contextual effect on healthy behavior with ICC= 27%. Conclusion: Healthy behavior in patients with hypertension increases with high education, participative in prolanis, strong family support, strong peer support, and female. Community health center has contextual effect on healthy behavior. Keywords: chronic disease management program, cerdik health behavior, hypertension. Correspondence: Tri Puji Pangesti. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: tripujipangesti8@gmail.com. Mobile: 082312657779. DOI: https://doi.org/10.26911/the7thicph.04.44
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Hamdan, Abeer, and Manar Abdel-Rahman. "Child Disciplinary Practices in relation to Household Head Education and beliefs in Five Middle East and North African (MENA) countries: Cross Sectional study-Further analysis of Multiple Indicator Cluster survey data." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0168.

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Introduction:Internationally, eight out of ten children are exposed to violent discipline by their caregivers. To reduce the prevalence of violent discipline against children, we should understand the social and economic factors that affect the choice of disciplinary methods. Despite the high prevalence of violent discipline in the Middle East and North African (MENA) region, only a few studies explored disciplinary methods in this region. Aim: This study aims to determine the prevalence of positive and violent disciplinary practices in five selected MENA countries and assess their association with household head education and beliefs of physical punishment. Methods: This is a cross-sectional study design based on available secondary data from the Multiple Indicator Cluster Survey on its fourth round (MICS-4). A child was selected randomly from the household, and the Parent-Child Conflict Scale (CTSPC) tool was used to report disciplinary methods the child encountered during the last month period preceding the survey. Univariate and multivariable logistic regression were used to investigate the association between disciplinary practices with household head education and respondent's beliefs of physical punishment. The analysis was conducted using pooled data from all selected surveys and also for individual countries. Result: The overall prevalence of positive discipline was only 15% (95% CI: 14.4-15.8), in the five countries, while the prevalence of violent discipline was 80% (95% CI: 79.0 -80.5). The prevalence of positive discipline was highest in Qatar (40%; 95% CI: 35.0-44.4) and lowest in Tunisia (5%; 95% CI: 4.3-5.9) while the prevalence of violent discipline was highest in Tunisia (93%; 95% CI: 92.1-94.1), and lowest in Qatar (50%; 95% CI: 44.7-55.0). Overall, the household head education was not significantly associated with either positive or violent discipline after adjusting for covariates. However, respondents believe of disciplinary methods was significantly associated with both positive and violent discipline (OR=5.88; 95% CI: 4.97-6.96) and (OR=6.27; 95% CI: 5.40-7.28), respectively. Conclusion: High rates of violent discipline in the MENA region might indicate an increase in mental, behavioral, and social problems and disorders in our future generation. Rapid action is needed to reduce the worsening of violent discipline, and it is consequences. There is a need for educational programs for caregivers to teach them alternative non-violent methods of discipline. Besides, these numbers should inform policymakers about the importance of the existence and the implementations of laws, policies, and regulations to protect children from all forms of violence to protect our future youths and ensure their health and wellbeing.
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Reports on the topic "Cross-sectional Regression"

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Robinson, Peter. Nonparametric trending regression with cross-sectional dependence. Institute for Fiscal Studies, February 2011. http://dx.doi.org/10.1920/wp.cem.2011.1011.

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Kan, Raymond, Cesare Robotti, and Jay Shanken. Pricing Model Performance and the Two-Pass Cross-Sectional Regression Methodology. Cambridge, MA: National Bureau of Economic Research, June 2009. http://dx.doi.org/10.3386/w15047.

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Villamizar-Villegas, Mauricio, and Yasin Kursat Onder. Uncovering Time-Specific Heterogeneity in Regression Discontinuity Designs. Banco de la República de Colombia, November 2020. http://dx.doi.org/10.32468/be.1141.

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The literature that employs Regression Discontinuity Designs (RDD) typically stacks data across time periods and cutoff values. While practical, this procedure omits useful time heterogeneity. In this paper we decompose the RDD treatment effect into its weighted time-value parts. This analysis adds richness to the RDD estimand, where each time-specific component can be different and informative in a manner that is not expressed by the single cutoff or pooled regressions. To illustrate our methodology, we present two empirical examples: one using repeated cross-sectional data and another using time-series. Overall, we show a significant heterogeneity in both cutoff and time-specific effects. From a policy standpoint, this heterogeneity can pick up key differences in treatment across economically relevant episodes. Finally, we propose a new estimator that uses all observations from the original design and which captures the incremental effect of policy given a state variable. We show that this estimator is generally more precise compared to those that exclude observations exposed to other cutoffs or time periods. Our proposed framework is simple and easily replicable and can be applied to any RDD application that carries an explicitly traceable time dimension.
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