User Preferences for Bicycle Infrastructure in Communities with Emerging Cycling Cultures

2019 ◽  
Vol 2673 (12) ◽  
pp. 89-102 ◽  
Author(s):  
Calvin Clark ◽  
Patricia Mokhtarian ◽  
Giovanni Circella ◽  
Kari Watkins
Keyword(s):  
United States ◽  
Linear Regression ◽  
Regression Models ◽  
User Preferences ◽  
Linear Regression Models ◽  
Bicycle Infrastructure

Non-motorized travel modes, particularly cycling, are experiencing a resurgence in many United States (U.S.) states as well as in other countries. Still, most studies focus on bicyclists’ behaviors in areas with strong bicycling cultures. This paper discusses the findings of a survey (N = 1,178) deployed in six communities in Alabama and Tennessee, U.S., where cycling is not (yet) popular nor widely adopted. The analysis includes linear regression models built on respondents’ reactions to images of bicycling infrastructure and their perceptions of being comfortable, safe, and willing to try cycling on the displayed roadway type. Findings indicate a preference for more separated bicycle infrastructure types along with options that exclude on-street parking. Segmented models indicate that, compared with potential cyclists, the preferences of regular utilitarian cyclists can vary more than those of recreational/occasional cyclists. Results from this study provide useful insights into ways to maximize the return on investments, and design bike infrastructure that can attract patronage and be most successful in areas lacking a substantial bicycling population.

scholarly journals Association rules and regression linear model of the groundwater population by the evaluation of uranium

2019 ◽  
Vol 270 ◽  
pp. 04017
Author(s):  
Iing Lukman ◽  
Natalina
Keyword(s):  
United States ◽  
Linear Regression ◽  
Association Rules ◽  
United States Of America ◽  
Regression Models ◽  
The United States ◽  
Total Alkalinity ◽  
Linear Regression Models ◽  
Five Factors ◽  
Groundwater Samples

The uranium available more on groundwater samples of certain types on the total alkalinity were relatively the same. But, the content of the uranium was higher in the samples. The multiple linear regression for pH as a dependent variable showed that the pH negatively correlated to the uranium, but the uranium was not significant for the linear regression model. The data of groundwater population from the samples of 127 with 12 variables of measurement of the Energy Department of the United States of America resulted in those association rules and linear regression models. The data has five factors of Producing horizon namely Ogallala Formation (TPO), Dockum Formation (TRD), Quartermaster Group (POQ), Whitehorse and Cloud Chief Group (PGWC), El Reno Group and Blaine Formation (PGEB). The step-wise linear regression for each of the five producing horizon codes was fitted to the data. Then, the regression models for each variable of producing horizon were obtained if pH was the dependent variable. If the Uranium was a dependent variable, then the regression models obtained were four only, with the model for PGEB was not able to be made. When pH as a dependent variable, it was depended upon Boron, Total alkalinity, and Bicarbonate.

Correlation of self-reported pain severity and healthcare expenditures in older United States adults

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
David R. Axon ◽  
Tyler Pesqueira ◽  
Briana Jarrell ◽  
Dominic Dicochea
Keyword(s):  
United States ◽  
Linear Regression ◽  
Healthcare Costs ◽  
Regression Models ◽  
Prescription Medication ◽  
Pain Severity ◽  
Moderate Pain ◽  
Linear Regression Models ◽  
Healthcare Expenditures ◽  
Extreme Pain

Abstract Objectives Healthcare expenditures of older United States (US) adults with different pain severity levels are important to investigate given the increasing prevalence of pain in this population. This study assessed the correlation of healthcare expenditures among older US adults with different pain severities, hypothesizing that expenditures would increase as pain severity increased. Methods This retrospective cross-sectional database study used 2018 Medical Expenditure Panel Survey (MEPS) data and included US adults aged ≥50 with self-reported pain in the past four weeks and positive healthcare costs. Adjusted linear regression models with logarithmically transformed expenditure data compared differences in: total; office-based; outpatient; emergency room; inpatient; other; and prescription medication expenditures, between those with little, moderate, quite a bit, and extreme pain. Analyses were weighted to account for the complex MEPS design and to obtain nationally representative estimates. The a priori alpha level was 0.05. Results The eligible sample of 5,123 individuals produced a weighted study population of 57,134,711 US adults aged ≥50 with pain (little = 53.1%, moderate = 21.6%, quite-a-bit = 18.5%, extreme = 6.8%). In adjusted linear regression models, compared to little pain, extreme pain had the greatest level of costs, followed by quite a bit pain and moderate pain, for total, office-based, and prescription medication costs. For instance, compared to little pain, total healthcare costs were 78% greater for those with extreme pain, 51% greater for quite a bit pain, and 37% greater for moderate pain. However, this pattern was not observed for outpatient, emergency room, inpatient, and other costs, where ≥1 comparison for each cost category was not statistically significant. Conclusions This study found total healthcare costs increased as pain severity increased, yet this was not always the case when analyzing subcategories of healthcare costs. Further research is needed to investigate why some types of healthcare costs are greater with increasing pain severity, yet others are not.

Impact of Package Descriptors on Young Adults' Perceptions of Cigarillos

2020 ◽  
Vol 6 (2) ◽  
pp. 118-135
Author(s):  
Abigail T. Evans ◽  
Jess Wilhelm ◽  
Haneen Abudayyeh ◽  
Lexie Perreras ◽  
Amy M. Cohn
Keyword(s):  
United States ◽  
Young Adults ◽  
Linear Regression ◽  
Perceived Risk ◽  
Regression Models ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Standard Errors ◽  
Linear Regression Models ◽  
Black And White

Objectives: In this study, we measured the effects of cigarillo packaging colors and flavor descriptors on appeal and perceived risk among young adults. Methods: United States-based young adults (ages 18-24) recruited via Amazon Mechanical Turk were randomized to view one of 7 images of cigarillo packages that varied in color (Black and White [B&W], brown, red) and flavor descriptor (none, tobacco, apple). Respondents rated the product's appeal, risk, and addictiveness. Differences in ratings by study condition were assessed using linear regression models with bootstrapped standard errors. Results: There were 2818 participants, and 26.5% reported having ever used a little cigar or cigarillo. Brown and red packaging were rated as more appealing (vs B&W) across 4 dimensions (all ps < .05). Compared to no flavor descriptor, tobacco flavor was rated as more "Attention-Grabbing" (b = 0.21, p = .010) and apple flavor was rated higher on all 8 measures of appeal (all ps < .05) and perceived as less addictive (b = -0.13, p = .024). Conclusions: Colors and flavor descriptors on cigarillo packaging increased appeal and decreased perceived addictiveness. Restricting color and flavor descriptors on packaging may reduce their appeal.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

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