scholarly journals Regression Model Evaluation for Highway Bridge Component Deterioration Using National Bridge Inventory Data

2016 ◽  
Author(s):  
Pan Lu ◽  
Shiling Pei ◽  
Denver Tolliver
Keyword(s):  
Model Evaluation ◽  
Regression Models ◽  
Goodness Of Fit ◽  
Evaluation Method ◽  
External Validation ◽  
Highway Bridges ◽  
Highway Bridge ◽  
Model Quality ◽  
National Bridge Inventory ◽  
Over Time

Accurate prediction of bridge component condition over time is critical for determining a reliable maintenance, repair, and rehabilitation (MRR) strategy for highway bridges. Based on bridge inspection data, regression models are the most-widely adopted tools used by researchers and state agencies to predict future bridge condition (FHWA 2007). Various regression models can produce quite different results because of the differences in modeling assumptions. The evaluation of model quality can be challenging and sometimes subjective. In this study, an external validation procedure was developed to quantitatively compare the forecasting power of different regression models for highway bridge component deterioration. Several regression models for highway bridge component rating over time were compared using the proposed procedure and a traditional apparent model evaluation method based on the goodness-of-fit to data. The results obtained by applying the two methods are compared and discussed in this paper.

scholarly journals Multivariate INAR(1) Regression Models Based on the Sarmanov Distribution

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 505
Author(s):  
Lluís Bermúdez ◽  
Dimitris Karlis
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Serial Correlation ◽  
Goodness Of Fit ◽  
Dependence Structure ◽  
Automobile Insurance ◽  
Data Set ◽  
New Models ◽  
Different Types ◽  
Over Time

A multivariate INAR(1) regression model based on the Sarmanov distribution is proposed for modelling claim counts from an automobile insurance contract with different types of coverage. The correlation between claims from different coverage types is considered jointly with the serial correlation between the observations of the same policyholder observed over time. Several models based on the multivariate Sarmanov distribution are analyzed. The new models offer some advantages since they have all the advantages of the MINAR(1) regression model but allow for a more flexible dependence structure by using the Sarmanov distribution. Driven by a real panel data set, these models are considered and fitted to the data to discuss their goodness of fit and computational efficiency.

scholarly journals Nonlinear quantile regression to describe the dry matter accumulation of garlic plants

2020 ◽  
Vol 50 (1) ◽  
Author(s):  
Guilherme Alves Puiatti ◽  
Paulo Roberto Cecon ◽  
Moysés Nascimento ◽  
Ana Carolina Campana Nascimento ◽  
Antônio Policarpo Souza Carneiro ◽  
...  
Keyword(s):  
Quantile Regression ◽  
Least Squares ◽  
Nonlinear Regression ◽  
Regression Models ◽  
Dry Matter ◽  
Goodness Of Fit ◽  
Least Squares Method ◽  
Ordinary Least Squares ◽  
Dry Matter Accumulation ◽  
Over Time

ABSTRACT: The objective of this study was to adjust nonlinear quantile regression models for the study of dry matter accumulation in garlic plants over time, and to compare them to models fitted by the ordinary least squares method. The total dry matter of nine garlic accessions belonging to the Vegetable Germplasm Bank of Universidade Federal de Viçosa (BGH/UFV) was measured in four stages (60, 90, 120 and 150 days after planting), and those values were used for the nonlinear regression models fitting. For each accession, there was an adjustment of one model of quantile regression (τ=0.5) and one based on the least squares method. The nonlinear regression model fitted was the Logistic. The Akaike Information Criterion was used to evaluate the goodness of fit of the models. Accessions were grouped using the UPGMA algorithm, with the estimates of the parameters with biological interpretation as variables. The nonlinear quantile regression is efficient for the adjustment of models for dry matter accumulation in garlic plants over time. The estimated parameters are more uniform and robust in the presence of asymmetry in the distribution of the data, heterogeneous variances, and outliers.

scholarly journals Prediction of Bridge Component Ratings Using Ordinal Logistic Regression Model

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Pan Lu ◽  
Hao Wang ◽  
Denver Tolliver
Keyword(s):  
Regression Model ◽  
External Validation ◽  
Highway Bridges ◽  
The United States ◽  
Information Criteria ◽  
Condition Rating ◽  
Validation Procedure ◽  
National Bridge Inventory ◽  
Error Bias ◽  
Akaike’S Information Criteria

Prediction of bridge component condition is fundamental for well-informed decisions regarding the maintenance, repair, and rehabilitation (MRR) of highway bridges. The National Bridge Inventory (NBI) condition rating is a major source of bridge condition data in the United States. In this study, a type of generalized linear model (GLM), the ordinal logistic statistical model, is presented and compared with the traditional regression model. The proposed model is evaluated in terms of reliability (the ability of a model to accurately predict bridge component ratings or the agreement between predictions and actual observations) and model fitness. Five criteria were used for evaluation and comparison: prediction error, bias, accuracy, out-of-range forecasts, Akaike’s Information Criteria (AIC), and log likelihood (LL). In this study, an external validation procedure was developed to quantitatively compare the forecasting power of the models for highway bridge component deterioration. The GLM method described in this study allows modeling ordinal and categorical dependent variable and shows slightly but significantly better model fitness and prediction performance than traditional regression model.

Do Materialistic Adolescents Ruminate More About Their Social Media Posts?

2020 ◽  
pp. 0044118X2098417
Author(s):  
Keeley Hynes ◽  
Daniel G. Lannin ◽  
Jeremy B. Kanter ◽  
Ani Yazedjian ◽  
Margaret M. Nauta
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Social Status ◽  
Mental Distress ◽  
External Validation ◽  
Value Orientation ◽  
Media Content ◽  
Over Time

Previous research suggests that ruminating on social media content is associated with greater mental distress (Yang et al., 2018). This study examined whether materialistic value orientation (MVO)—prioritizing values and goals related to consumerism, consumption, and social status—predicted social media rumination in a sample of diverse adolescents in a two-wave cross-lagged design. A cross-lagged analysis among 119 adolescents indicated that MVO at Wave 1 predicted greater social media rumination 4 months later at Wave 2, but social media rumination at Wave 1 did not predict MVO at Wave 2. Cross-lagged results suggested that MVO may lead to greater social media rumination over time for diverse adolescents. Adolescents with MVO could benefit from interventions to reduce the effects of their need for external validation and maladaptive rumination, as external validation and maladaptive rumination are linked to behaviors and thoughts that can be harmful to mental health.

Changing Attitudes Toward Euthanasia and Suicide for Terminally Ill Persons, 1977 to 2016

2017 ◽  
Vol 80 (3) ◽  
pp. 355-379 ◽  
Author(s):  
Brandon K. Attell
Keyword(s):  
Regression Models ◽  
Sociological Theory ◽  
Terminally Ill ◽  
Cohort Effects ◽  
Logistic Regression Models ◽  
Period Effects ◽  
Changing Attitudes ◽  
Biased Estimates ◽  
Analysis Point ◽  
Over Time

Several longitudinal studies show that over time the American public has become more approving of euthanasia and suicide for terminally ill persons. Yet, these previous findings are limited because they derive from biased estimates of disaggregated hierarchical data. Using insights from life course sociological theory and cross-classified logistic regression models, I better account for this liberalization process by disentangling the age, period, and cohort effects that contribute to longitudinal changes in these attitudes. The results of the analysis point toward a continued liberalization of both attitudes over time, although the magnitude of change was greater for suicide compared with euthanasia. More fluctuation in the probability of supporting both measures was exhibited for the age and period effects over the cohort effects. In addition, age-based differences in supporting both measures were found between men and women and various religious affiliations.

scholarly journals External validation of the European risk assessment tool for cardio metabolic disease in a Middle Eastern population

2020 ◽  
Author(s):  
Samaneh Asgari ◽  
Fatemeh Moosaie ◽  
Davood Khalili ◽  
Fereidoun Azizi ◽  
Farzad Hadaegh
Keyword(s):  
Metabolic Disease ◽  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Goodness Of Fit ◽  
Assessment Tool ◽  
External Validation ◽  
Iranian Population ◽  
Risk Assessment Tool ◽  
Goodness Of Fit Test

Abstract Background: High burden of chronic cardio-metabolic disease (CCD) including type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and cardiovascular disease (CVD) have been reported in the Middle East and North Africa region. We aimed to externally validate a Europoid risk assessment tool designed by Alssema et al, including non-laboratory measures, for the prediction of the CCD in the Iranian population. Methods: The predictors included age, body mass index, waist circumference, use of antihypertensive, current smoking, and family history of cardiovascular disease and or diabetes. For external validation of the model in the Tehran lipids and glucose study (TLGS), the Area under the curve (AUC) and the Hosmer-Lemeshow (HL) goodness of fit test were performed for discrimination and calibration, respectively. Results: Among 1310 men and 1960 women aged 28-85 years, 29.5% and 47.4% experienced CCD during the 6 and 9-year follow-up, respectively. The model showed acceptable discrimination, with an AUC of 0.72(95% CI: 0.69-0.75) for men and 0.73(95% CI: 0.71-0.76) for women. The calibration of the model was good for both genders (min HL P=0.5). Considering separate outcomes, AUC was highest for CKD (0.76(95% CI: 0.72-0.79)) and lowest for T2DM (0.65(95% CI: 0.61-0.69)), in men. As for women, AUC was highest for CVD (0.82(95% CI: 0.78-0.86)) and lowest for T2DM (0.69(95% CI: 0.66-0.73)). The 9-year follow-up demonstrated almost similar performances compared to the 6-year follow-up. Conclusion: This model showed acceptable discrimination and good calibration for risk prediction of CCD in short and long-term follow-up in the Iranian population.

Abstract P372: Coronary Angiography Use, Results and Revascularization Trends in Olmsted County, Minnesota, 2000 to 2015

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Yariv L Gerber ◽  
Susan Weston ◽  
Jill Killian ◽  
Matteo Fabbri ◽  
Sheila Manemann ◽  
...  
Keyword(s):  
Coronary Angiography ◽  
Regression Models ◽  
Direct Method ◽  
Coronary Revascularization ◽  
Temporal Trends ◽  
Olmsted County ◽  
Left Main ◽  
Logistic Regression Models ◽  
Over Time ◽  
Age And Sex

Background: A decline in all forms of coronary revascularization has been previously reported. Whether the decline has continued after the turn of the century is unknown as well as whether it is influenced by trends in the use and results of coronary angiography. Methods: All diagnostic and therapeutic coronary procedures performed among Olmsted County, MN residents from 2000-2015 were analyzed. Standardized rates (per 100,000 population) were calculated applying the direct method and temporal trends compared using Poisson regression models. Trends in disease severity, defined as 3-vessel and/or left main coronary artery disease (CAD), were assessed using logistic regression models. Results: Between 2000 and 2015, 11,691 coronary angiographies were performed (63% men; 54% ≥ 65 years of age). The age- and sex-standardized rates of angiography decreased over time (p trend < 0.001; Figure). Overall, 30% of the subjects had 3-vessel and/or left main CAD, and this proportion decreased over time (age- and sex-adjusted odds ratios (95% CI) for severe CAD: 0.68 (0.62-0.76) in 2005-2009 and 0.69 (0.63-0.77) in 2010-2015 compared with 2000-2004). Among 5,222 coronary revascularization procedures performed, 78% were PCI and 22% CABG. The age- and sex-standardized rates of any revascularization declined during the study period, reflecting temporal decreases in both PCI and CABG (all p trend < 0.001; Figure). The declines in angiography rates, CAD severity, and revascularization utilization were consistently greater in women than men (all P for interactions < 0.01). Conclusions: Declines in all forms of coronary revascularization, which were greater in women than men, have occurred in Olmsted County, MN, from 2000-2015. The declines occurred in the context of fewer angiograms performed in the population and reduced severity of anatomic CAD.

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