Research paper | 31-October-2017
Evaluating the effect of variables on diagnostic measures (sensitivity, specificity, positive, and negative predictive values) is often of interest to clinical researchers. Logistic regression (LR) models can be used to predict diagnostic measures of a screening test. A marginal model framework using generalized estimating equation (GEE) with logit/log link can be used to compare the diagnostic measures between two or more screening tests. These individual modeling approaches to each diagnostic
Alok Kumar Dwivedi,
Indika Mallawaarachchi,
Juan B. Figueroa-Casas,
Angel M. Morales,
Patrick Tarwater
Statistics in Transition New Series, Volume 16 , ISSUE 2, 203–222
Article | 31-December-2020
the highest mortality rates gathered for the period 2016-2018. Owing to the dichotomous form of the studied variable, logistic regression was used. Estimated model parameters and calculated odds ratios allowed to assess the effect of selected factors on road traffic mortality rate. As significant, the type of the perpetrator and the traffic participant, sex and age of the victim, road lighting, and the driver’s experience were selected. It was assessed that pedestrians are the group most
Anna BORUCKA,
Małgorzata GRZELAK,
Andrzej ŚWIDERSKI
Transport Problems, Volume 15 , ISSUE 4, Part 1, 125–136
Article | 11-March-2018
railway crossing, and the maximum speed of trains. Applying the binary model of logistic regression, the probability of accidents at the 337 railway crossings of the country was calculated. Depending on the degree of risk or the probability of accident, the country's railway crossings are ranked. The most dangerous crossings of four regions in the country were identified. Finally, the main conclusions and recommendations are presented.
Gintautas BUREIKA,
Marek KOMAIŠKO,
Virgilijus JASTREMSKAS
Transport Problems, Volume 12 , ISSUE SE, 11–22
Original Paper | 09-October-2019
;, Immucor, Warren, NJ) was performed on all patient specimens referred for molecular testing over 45 months; serologic and clinical data were analyzed. We used simple and multiple logistic regression to model the risk factors for alloimmunization to an HIA. Of the 2591 patients genotyped, 32 (1.2%) were homozygous for at least one variant predicting absence of an HIA. Of these 32 patients, prior transfusion or pregnancy history was available for 29 (91%). Four susceptible patients made an antibody to an
Patricia A.R. Brunker,
Keerthana Ravindran,
R. Sue Shirey
Immunohematology, Volume 33 , ISSUE 1, 9–14
Article | 06-July-2017
In this study the benefits arising from the use of the Bayesian approach to predictive modelling will be outlined and exemplified by a linear regression model and a logistic regression model. The impact of informative and non-informative prior on model accuracy will be examined and compared. The data from the Central Statistical Office of Poland describing unemployment in individual districts in Poland will be used. Markov Chain Monte Carlo methods (MCMC) will be employed in modelling.
Wioletta Grzenda
Statistics in Transition New Series, Volume 17 , ISSUE 4, 763–780
Original Paper | 04-December-2017
student t test, as appropriate. Multivariate analysis using logistic regression was conducted to assess the association between influencing factors and S. aureus and MRSA nasal carriage. 1010 diabetic participants were included in the study. The prevalence of S. aureus and MRSA nasal carriage were 28.32% and 1.09%, respectively. After the logistic regression, ever had a painful sensation or tingling in hands or feet past three months (Odds Ratio [OR] = 0.359, 95% Confidence Interval [CI], 0.146
Jialing Lin,
Yang Peng,
Chan Bai,
Ting Zhang,
Haoqu Zheng,
Xiaojie Wang,
Jiaping Ye,
Xiaohua Ye,
Ying Li,
Zhenjiang Yao
Polish Journal of Microbiology, Volume 66 , ISSUE 4, 439–448
Article | 03-March-2021
Danutė Krapavickaitė
Statistics in Transition New Series, Volume 22 , ISSUE 1, 197–206
Article | 24-June-2021
study owing to its high requirement of rural transport infrastructure. Questionnaires were sent to 438 households. An analysis of data was performed descriptively and with logistic regression. Community participation was recorded as financial, labor, material, and land contribution. Household composition, education, income, and member in household as community leader are among the highest influential factors to community participation. With the importance of community participation, the results of
Dinh Tuan HAI,
Nguyen Xuan QUYET,
Duc Anh NGUYEN
Transport Problems, Volume 16 , ISSUE 2, 45–57
Research Article | 04-September-2019
Olga Komorowska,
Arkadiusz Kozłowski,
Teresa Słaby
Statistics in Transition New Series, Volume 20 , ISSUE 3, 97–117
book-review | 19-August-2019
. Bivariate associations were studied using binomial logistic regression results shown as odds ratios with 95 % confidence intervals. Delinquency was entered as dependent variable. In the first model, categorical time periods (2000-2001, 2002-2003, 2004-2005, 2006-2007, 2008-2009, 2010-2011, 2012-2013, 2014-2015) were entered as independent factors using the time period 2000-2001 as a reference category. In the second model, family structure (living with both parents/other), parental unemployment in the
Noora Knaappila,
Mauri Marttunen,
Sari Fröjd,
Nina Lindberg,
Riittakerttu Kaltiala-Heino
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 7 , 52–59
Article | 03-March-2021
. Since the Altman Z-Score model was devised, numerous studies on bankruptcy prediction have been written. Most of them involve the application of traditional methods, including linear discriminant analysis (LDA), logistic regression and probit analysis. However, most recent studies in the area of bankruptcy prediction focus on more advanced methods, such as case-based reasoning, genetic algorithms and neural networks. In this paper, the effectiveness of LDA and SVM predictions were compared. A sample
Aneta Ptak-Chmielewska
Statistics in Transition New Series, Volume 22 , ISSUE 1, 179–195
research-article | 30-November-2018
variables) were calculated for all outcomes and covariates. Multivariate logistic regression analyses were performed to examine associations of network features with each prevention and sex behavior outcome, while also controlling for individual and structural factors. Adjusted odds ratios (aORs) and their 95% confidence intervals (95% CIs) were calculated. All models were fit using RDS sampling weights, specifically Gile’s Sequential Sampling (SS) estimator (Gile, 2011; Gile & Handcock, 2010), an
Lindsay E. Young,
Kayo Fujimoto,
Leigh Alon,
Liang Zhang,
John A. Schneider
Journal of Social Structure, Volume 20 , ISSUE 3, 70–95
Research Article | 05-July-2017
depression.Results:In 55% of participants, intoxication was by alcohol consumption. Deliberate self-harm was found in 17% of the participants. Of the 138 adolescents, 39% scored positive on the BDI for depressive symptoms, occurring more commonly in girls. Logistic regression showed that the most significant variables associated with depressive symptoms were female gender, high psychological distress, and low self-esteem. Symptoms of depression served as a mediator between gender and self-esteem and the blood
Varpu Puuskari,
Terhi Aalto-Setälä,
Erkki Komulainen,
Mauri Marttunen
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 5 , ISSUE 1, 39–49
research-article | 12-January-2022
).
Statistical analyses
All statistical analyses were performed using JMP® Pro version 14 (SAS Institute Inc., Cary, NC, USA). Demographic characteristics were expressed as means and standard deviations for continuous variables and as frequencies and percentages for categorical variables. Chi-squared and Wilcoxon rank sum tests were used to compare differences between groups. Logistic regression analyses were performed to calculate the adjusted odds ratio (OR) with 95% confidence interval (CI) for evaluating
Chika Ueno,
Shuichi Yamamoto
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 10 , 1–8
Research Article | 30-November-2013
obtained data from 2765 adolescents who were in grade 9 in Denmark at that time. Logistic regression was used to assess the association between the outcome variable of binge drinking and the exposure variables of alcohol-drinking peers, pocket money, and mother’s/father’s approval of intoxication.The risk of binge drinking increased with the number of alcohol-drinking peers (trend test, p < .0001) and with the amount of pocket money spent (trend test, p < .0001. The association between the
Maria Pedersen,
Per Kragh Andersen,
Svend Sabroe
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 2 , ISSUE 3, 135–142
Article | 20-July-2021
. Further analysis using logistic regression showed that the orthodontists’ years of experience did not influence the accuracy of skeletal diagnosis (p = 0.177). A comparison between the orthodontists’ dental (p = 0.689) and skeletal (p = 0.321) determinations did not significantly differ between the two groups. An assessment of the vertical growth pattern (p = 0.656) was also unaffected by the omission of the lateral cephalometric radiograph. When the two groups considered treatment
Scott Derek Currell,
Sophie May Roberts,
Yousef Abdalla,
Adrian Esterman
Australasian Orthodontic Journal, Volume 34 , ISSUE 2, 188–195
research-article | 30-November-2019
statistical software (version 23). We used a binary logistic regression method in which an Odds Ratio can be calculated for a nominal dependent variable (for example, smoking cigarette: 1-Yes, 0-No) through combination of several independent variables. In this study, we used traditional and cyber victimization and gender as predictors for substance use, self-harm, and suicide. The statistical significance level was considered as p < 0.05.
As some of the students did not properly answer the questions, 25
Mohammad Saeed Azami,
Farhad Taremian
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 8 , 101–109
research-article | 30-November-2019
cisgender and transgender adolescents using cross-tabulations with chi-square statistics/Fisher’s exact test where appropriate. Next, multivariate associations were studied using logistic regression. The sexual experiences, sexual harassment and dating violence variables were entered each in turn as the dependent variable. Gender identity was entered as the independent variable, age (continuous) and sex were controlled for. Next, the sincerity screening variable was added into the analyses, and finally
Elias Heino,
Sari Fröjd,
Mauri Marttunen,
Riittakerttu Kaltiala
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 8 , 166–175
research-article | 04-January-2021
mediator at time t2, and the dependent variable at time t3, with t1 < t2 < t3. Whether the mediator was present before the outcome variable is an assumption that is made, as we cannot know with complete certainty that the DSH did not begin before the age of 11, when the peer difficulties were measured. In the mediation analysis, the significant variables from the logistic regression were included as control variables. A bootstrap approach was applied to create confidence intervals (67). All statistical
Therese A. Evald,
Bo Møhl
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 8 , 176–188
research-article | 23-April-2021
-up at the CAP clinic and the Control group in a quiet room at their school or at the CAP clinic. For both groups, the WISC-IV/WAIS-IV assessments were carried out by fully qualified neuropsychologists or supervised clinical psychology students trained to administer these scales.
Statistical analyses
Between group comparisons, differences between composites and logistic regression analyses were carried out using version 25 of SPSS (IBM Corp., Armonk, NY, USA). Linear mixed model regression
Pia Tallberg,
Maria Rastam,
Sean Perrin,
Anne-Li Hallin,
Peik Gustafsson
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 9 , 52–63
Research Article | 30-November-2013
subgroups of preadolescent emotional problems. Multinomial logistic regressions were conducted to assess the relationships between these subgroups and the presence of an immigrant background with four immigrant groups (all backgrounds, Pakistan, Turkey, and Sri Lanka). The reference group was the ethnic Norwegians.LCA identified three classes according to the severity of the problems; these were labeled healthy, borderline, and distressed. Multinomial logistic regression analyses found the presence of
Daniele E. Alves,
Heather L. Corliss,
Espen Roysamb,
Henrik D. Zachrisson,
Brit Oppedal,
Kristin Gustavson
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Volume 2 , ISSUE 1, 41–51