Commentary on “Letter to the Editor for Article Titled Predictive Factors for Postherpetic Neuralgia Using Ordered Logistic Regression Analysis”

2013 ◽  
Vol 29 (12) ◽  
pp. 1098
Author(s):  
Yuko Kanbayashi ◽  
Keiko Ohnishi ◽  
Toyoshi Hosokawa
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Postherpetic Neuralgia ◽  
Letter To The Editor ◽  
Ordered Logistic Regression

Predictive Factors for Postherpetic Neuralgia Using Ordered Logistic Regression Analysis

2012 ◽  
Vol 28 (8) ◽  
pp. 712-714 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Keiko Onishi ◽  
Keita Fukazawa ◽  
Kousuke Okamoto ◽  
Hiroshi Ueno ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Postherpetic Neuralgia ◽  
Ordered Logistic Regression

Predictive factors for taxane acute pain syndrome determined by ordered logistic regression analysis

2018 ◽  
Vol 27 (7) ◽  
pp. 2673-2677 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Kouichi Sakaguchi ◽  
Katsuhiko Nakatsukasa ◽  
Yoshimi Ouchi ◽  
Yusuke Tabuchi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Acute Pain ◽  
Pain Syndrome ◽  
Ordered Logistic Regression

Predictive factors in patients eligible for pegfilgrastim prophylaxis focusing on RDI using ordered logistic regression analysis

2018 ◽  
Vol 35 (4) ◽  
Author(s):  
Yuko Kanbayashi ◽  
Takeshi Ishikawa ◽  
Motohiro Kanazawa ◽  
Yuki Nakajima ◽  
Rumi Kawano ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Ordered Logistic Regression

Predictive factors for sorafenib-induced hand–foot skin reaction using ordered logistic regression analysis

2016 ◽  
Vol 73 (1) ◽  
pp. e18-e23 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Toyoshi Hosokawa ◽  
Kohichiroh Yasui ◽  
Fumiya Hongo ◽  
Kanji Yamaguchi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Skin Reaction ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Ordered Logistic Regression ◽  
Hand Foot Skin Reaction

Predictive factors for the development of irinotecan-related cholinergic syndrome using ordered logistic regression analysis

2018 ◽  
Vol 35 (6) ◽  
Author(s):  
Yuko Kanbayashi ◽  
Takeshi Ishikawa ◽  
Motohiro Kanazawa ◽  
Yuki Nakajima ◽  
Yusuke Tabuchi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Ordered Logistic Regression ◽  
Cholinergic Syndrome

Trust in police as an influencing factor on trust in government: 2SLS analysis using perception of safety

2020 ◽  
Vol 43 (4) ◽  
pp. 541-558
Author(s):  
Jisu Jeong ◽  
Seunghui Han
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Trust In Government ◽  
Content Type ◽  
Perception Of Safety ◽  
Ordered Logistic Regression ◽  
The Impact ◽  
The Relationship ◽  
Trust In Police

PurposeCitizen trust in police is important in terms of citizen consent to government policies and of police achieving their organizational goals. In the previous study, improvements in police policy, organizational operation and policing activities were developed to clarify which factors influence trust in police and how trust can be improved. This research raises the question, would changes in trust in police have an impact on trust in government? In this paper, this research question is discussed theoretically and the causal relationship analyzed empirically by applying OLS, ordered logistic, 2SLS and logistic regressions.Design/methodology/approachThe basic analysis methods are to apply the OLS and the ordered logistic regression. OLS regression analysis is an analytical method that minimizes an error range of a regression line. The assumptions for OLS are: linearity, independence, equilibrium, extrapolation and multicollinearity issues. These problems were statistically verified and analyzed, in order to confirm the robustness of the analysis results by comparing the results of the ordered logistic regression because of the sequence characteristic of the dependent variable. The data to be used in this study is the Asia Barometer Survey in 2013.FindingsTrust in police and citizen perception of safety are analyzed as important factors to increase trust in the government. The effects of trust in police are more significant than the effects of control variables, and the direction and strength of the results are stable. The effect of trust in police on trust in government is strengthened by the perception of safety (IV). In addition, OLS, ordered logistic regression analysis, which analyzed trust in central government and local government, and logistic regression analysis categorized by trust and distrust show the stability.Research limitations/implicationsThis paper has implications in terms of theoretical and empirical analysis of the relationship between trust in police and trust in government. In addition, the impact of perception of safety on trust in police can be provided to police officers, policymakers and governors who are seeking to increase trust in government. This paper is also meaningful in that it is the microscopic research based on the citizens' survey. One of the limitations of macroscopic research is that it does not consider the individual perceptions of citizens.Practical implicationsThe results of this paper can confirm the relationship of the virtuous cycle, which is perception of safety – trust in police – trust in government. The police will need to provide security services to improve citizens' perception of safety and make great efforts to create safer communities and society. Trust in police formed through this process can be an important component of trust in government. By making citizens feel safer and achieving trust in police, ultimately, trust in government will be improved.Originality/valueThe police perform one of the essential roles of government and are one of the major components of trust in government, but the police sector has been neglected compared to the roles of the economic and political sectors. These influences of macro factors are too abstract to allow specific policy directions to be suggested. If we consider trust in police, and factors that can improve trust in government, we can suggest practical policy alternatives.

scholarly journals Ectopic eruption of the maxillary second molar: Predictive factors

2017 ◽  
Vol 87 (4) ◽  
pp. 583-589 ◽  
Author(s):  
Soonshin Hwang ◽  
Yoon Jeong Choi ◽  
Ji Yeon Lee ◽  
Chooryung Chung ◽  
Kyung-Ho Kim
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Multivariate Logistic Regression Analysis ◽  
Key Factors ◽  
Multivariate Logistic Regression ◽  
Factors Associated ◽  
Ectopic Eruption ◽  
Maxillary Tuberosity

ABSTRACT Objective: The purpose of this study was to investigate the diagnostic aspects, contributing conditions, and predictive key factors associated with ectopic eruption of maxillary second molars. Material and Methods: This retrospective study evaluated the study models, lateral cephalographs, and panoramic radiographs of 40 adult subjects (20 men, 20 women) with bilateral ectopic eruption and 40 subjects (20 men, 20 women) with normal eruption of the maxillary second molars. Studied variables were analyzed statistically by independent t-tests, univariate and multivariate logistic regression analysis, followed by receiver-operating characteristic analysis. Results: Tooth widths of bilateral lateral incisors, canines, and premolars were wider in the ectopic group, which resulted in greater arch lengths. The ANB angle and maxillary tuberosity distance (PTV-M1, PTV-M2) were smaller in the ectopic group. The long axes of the maxillary molars showed significant distal inclination in the ectopic group. The multivariate logistic regression analysis showed that three key factors—arch length, ANB angle, and PTV-M1 distance—were significantly associated with ectopic eruption of the second molars. The area under the curve (AUC) was the largest for the combination of the three key factors with an AUC greater than 0.75. PTV-M1 alone was the single factor that showed the strongest association with ectopic eruption (AUC = 0.7363). Conclusions: An increase in arch length, decrease in ANB angle, and decrease in maxillary tuberosity distance to the distal aspect of the maxillary first molar (PTV-M1) were the most predictive factors associated with ectopic eruption of maxillary second molars.

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