on learning. In the current study, within the framework of an observational methodology design ( Anguera, 1979 ), we applied a series of logisticregression models to investigate whether F-7 or F-8 was better suited to the learning needs of children aged 8-10 years moving up from futsal (F-5). The matches analyzed took place at the end of the 2011-2012 season between teams about to move up from F-5 to the newly introduced F-8 format. Considering the multiple dichotomous variables of interest in studies of sport, together with the potential offered by logistic
). Applied logisticregression John Wiley & Sons. 4. Dobek A., Moliński K., Skotarczak E. Porównanie mocy testów Rao’s score, Walda i ilorazu największej wiarogodności dla tablicy kontyngencji wymiaru (2xc). Biometrical Letters, 2015. 5. Domencich, Thomas A., and Daniel McFadden. Urban travel demand-a behavioral analysis. No. Monograph. 1975. 6. Davis, B. C. “Factors affecting choice of travel mode.” Australian Road Research Board Conference Proc. Vol. 7. No. 2. 1975.
This paper deals with the primary causes of informal housing in Greece as well as the observed differentiations in informal housing patterns across space. The spatial level of analysis is the prefectural administrative level. The results of the multinomial logistic regression analysis indicate that Greek prefectures differ in the way they experience the informal housing phenomenon. An explanation for the observed differences may be the separate development paths followed and the diverse range of economic activities in each prefecture. The Greek state has not made provisions for creating the necessary ‘urban land stock’ in each prefecture, so that everyone interested can find land parcels at an affordable price. On the contrary, the state encourages the informal housing activity by legalizing large areas of such activity sporadically and by introducing legislative initiatives of limited success in dealing with the problem.
References Aktywność ekonomiczna ludności Polski IV kwartał 2010 (2011), Informacje i opracowania statystyczne, Warszawa: Główny Urząd Statystyczny. Cramer, J.S. (2002), The Origins of LogisticRegression , Tinbergen Institute Discussion Paper, Faculty of Economics and Econometrics, University of Amsterdam. Hosmer, D.W., Lemeshow, S. (2000), Applied LogisticRegression , John Wiley & Sons, Inc. Kleinbaum, D.G., Klein, M. (2002), LogisticRegression. A Self-Lerning Text. Second Edition , Springer-Verlag, New York, Berlin, Heidelberg. Long, J.S. (1997
Objective This study was undertaken to investigate the influencing factors on serum ALT level and hepatitis C virus (HCV) RNA titer in chronic hepatitis C (CHC) patients.
Methods All patients enrolled into this study were anti-HCV positive. Retrospective tracing method was applied to detect serum ALT level and HCV RNA titer and to collect general information of the patients such as genders, age groups, interferon medication history, infection pathways, height and weight. Then the multi-factor analysis was adopted with the application of binominal logistic regression mode.
Results The abnormal rate of ALT level was positively correlated to HCV RNA and gender while negatively correlated to interferon medication history and age group, with Wald value of the 4 factors as 39.604, 11.823, 18.991 and 7.389, respectively. The positive rate of HCV RNA was negatively correlated to interferon medication history and gender while positively correlated to ALT level, with corresponding Wald value of the 3 factors as 81.394, 7.618 and 27.562, respectively.
Conclusions The normal ALT level in HCV infected patients was associated with viral load, age, gender and interferon medication history, while the normal rate of HCV RNA titer was closely associated with gender, interferon medication history and ALT level.
). Applying a Hybrid Model of Markov Chain and LogisticRegression to Identify Future Urban Sprawl in Abouelreesh, Aswan: A Case Study. Geosciences , 6 (4), 1-17. doi:10.3390/geosciences6040043 Kambour, E. (2003). PPT. Edward Kambour. Retrieved from http://www.kambour.net/football.ppt Knottenbelt, W. J., Spanias, D., & Madurska, A. M. (2012). A common-opponent stochastic model for predicting the outcome of professional tennis matches. Computers & Mathematics with Applications , 64 (12), 3820-3827. Kvam, P. and J.S. Sokol (2006). A logisticregression/Markov chain model
Gecikmelerin Lojistik Regresyon Analizi ile Belirlenmesi. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı, Adana. Bilgin L., Taşçı D,.Kağnıcıoğlu D., Benligiray S., Tonus H.Z. (2004). Insan Kaynakları Yönetimi. Anadolu Üniversitesi Yayınları. Eskişehir. s.3. Girginer N., Cankuş, B. (2008). The Measurement of Satisfaction Level of Citizens About Municipality Services. Eskişehir Osmangazi University, Institute of Social Sciences. Eskişehir. Çırak, G. (2012). The Usage of Artificial Neural Networks and LogisticRegression Methods in the Classification of
examined the influence of the goalkeeper on ball possession effectiveness. Therefore, the aim of the present study was to identify the impact of playing 4 vs. 4 or 5 vs. 4 on ball possession effectiveness in futsal and to determine the best predictors (i.e., space and task related indicators and situational variables) of success in futsal ball possession using the binomial logisticregression. It was hypothesized that ball possession effectiveness in futsal was dependent on space and task performance indicators as well as situational variables and that teams using the 5
Interleukin-6 and interleukin-8 are early biomarkers of acute kidney injury and predict prolonged mechanical ventilation in children undergoing cardiac surgery: a case-control study, Critical Care, Vol. 13, pp. R104, , 2009  P. Peduzzi, J. Concato, E. Kemper, T.R. Holford, A.R. Feinstein, A simulation study of the number of events per variable in logisticregression analysis, Journal of Clinical Epidemiology, Vol. 49, pp. 1373-1379, 1996  A. Petrie, C. Sabin, Statystyka medyczna w zarysie, (In Polish)Wydawnictwo Lekarskie PZWL, Warszawa 2006  A. Stanisz
Kaufmann Publishers, Second Edition, 21–27. 9. Harrell F. (2001), Regression Modeling Strategies with Applications to Linear Models , LogisticRegression, and Survival Analysis, Springer-Verlag, New York. 10. Hauser W., Hoffmn J., Kuhbacher T., Raible A., Reinshagen M., Rogler G., Schreiber S., Neukamm U., Eceterski A. (2007), Crohn's disease and other inflammatory bowel diseases (In Polish: Choroba Lesniowskiego - Crohna i inne nieswoiste zapalenia jelit) , Wydawnictwo Lekarskie PZWL. 11. Hosmer D., Lemeshow S., Sturdivant R. (2013), Applied LogisticRegression