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Wyszukujesz frazę "Multinomial Logistic Regression" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Informal Housing in Greece: A Multinomial Logistic Regression Analysis at the Regional Level
Autorzy:
POLYZOS, Serafeim
MINETOS, Dionysios
Powiązania:
https://bibliotekanauki.pl/articles/623885.pdf
Data publikacji:
2014-01-22
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
informal housing
land use changes
multinomial logistic regression
housing policy
Greece
Opis:
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.
Źródło:
European Spatial Research and Policy; 2013, 20, 2
1231-1952
1896-1525
Pojawia się w:
European Spatial Research and Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multinomial Logistic Regression Approach For The Evaluation Of Binary Diagnostic Test In Medical Research
Autorzy:
Dwivedi, Alok Kumar
Mallawaarachchi, Indika
Figueroa-Casas, Juan B.
Powiązania:
https://bibliotekanauki.pl/articles/465774.pdf
Data publikacji:
2015
Wydawca:
Główny Urząd Statystyczny
Tematy:
multinomial logistic regression predictive values
sensitivity, specificity
acute appendicitis
pulmonary abnormalities
medical diagnostic test
Opis:
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 measure ignore the dependency among these measures that might affect the association of covariates with each diagnostic measure. The diagnostic measures are computed using joint distribution of screening test result and reference test result which generates a multinomial response data. Thus, multinomial logistic regression (MLR) is a more appropriate approach to modeling these diagnostic measures. In this study, the validity of LR and GEE approaches as compared to MLR model was assessed for modeling diagnostic measures. All methods provided unbiased estimates of diagnostic measures in the absence of any covariate. LR and GEE methods produced more biased estimates as compared to MLR approach especially for small sample size studies. No bias was obtained in predicting sensitivity measure using MLR method for one screening test. Our proposed MLR method is robust for modeling diagnostic measures of a screening test as opposed to LR method. MLR method and GEE method produced similar estimates of diagnostic measures for comparing two screening tests in large sample size studies. The proposed MLR model for diagnostic measures is simple, and available in common statistical software. Our study demonstrates that MLR method should be preferred as an alternative for modeling diagnostic measures.
Źródło:
Statistics in Transition new series; 2015, 16, 2; 203-222
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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