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Wyszukujesz frazę "misclassification" wg kryterium: Wszystkie pola


Wyświetlanie 1-5 z 5
Tytuł:
A new method for identifying outlying subsets of data
Autorzy:
Zalewska, M.
Grzanka, A.
Niemiro, W.
Samoliński, B.
Powiązania:
https://bibliotekanauki.pl/articles/970610.pdf
Data publikacji:
2008
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
misclassification error
discriminant analysis
multidimensional homogeneity test
medical data
Opis:
In various branches of science, e.g. medicine, economics, sociology, it is necessary to identify or detect outlying subsets of data. Suppose that the set of data is partitioned into many relatively small subsets and we have some reason to suspect that one or several of these subsets may be atypical or aberrant. We propose applying a new measure of separability, based on the ideas borrowed from the discriminant analysis. In our paper we define two versions of this measure, both using a jacknife, leave-one-out, estimator of classification error. If a suspected subset is significantly well separated from the main bulk of data, then we regard it as outlying. The usefulness of our algorithm is illustrated on a set of medical data collected in a large survey "Epidemiology of Allergic Diseases in Poland" (ECAP). We also tested our method on artificial data sets and on the classical IRIS data set. For a comparison, we report the results of a homogeneity test of Bartoszyński, Pearl and Lawrence, applied to the same data sets.
Źródło:
Control and Cybernetics; 2008, 37, 3; 693-709
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Joint Calibration Estimator for dual frame surveys
Autorzy:
Elkasabi, Mahmoud A.
Heeringa, Steven G.
Lepkowski, James M.
Powiązania:
https://bibliotekanauki.pl/articles/465638.pdf
Data publikacji:
2015
Wydawca:
Główny Urząd Statystyczny
Tematy:
dual-frame estimation
calibration weighting
auxiliary variables
domain misclassification
Opis:
Many dual frame estimators have been proposed in the statistics literature. Some of these estimators are theoretically optimal but hard to apply in practice, whereas others are applicable but have larger variances than the first group. In this paper, a Joint Calibration Estimator (JCE) is proposed that is simple to apply in practice and meets many desirable properties for dual frame estimators. The JCE is asymptotically design unbiased conditional on the strong relationship between the estimation variable and the auxiliary variables employed in the calibration. The JCE achieves better performance when the auxiliary variables can fully explain the variability in the study variables or at least when the auxiliary variables are strong correlates of the estimation variables. As opposed to the standard dual frame estimators, the JCE does not require domain membership information. Even if included in the JCE auxiliary variables, the effect of the randomly misclassified domains does not exceed the random measurement error effect. Therefore, the JCE tends to be robust for the misclassified domains if included in the auxiliary variables. Meanwhile, the misclassified domains can significantly affect the unbiasedness of the standard dual frame estimators as proved theoretically and empirically in this paper.
Źródło:
Statistics in Transition new series; 2015, 16, 1; 7-36
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Validity test of the IPD-Work consortium approach for creating comparable job strain groups between Job Content Questionnaire and Demand-Control Questionnaire
Autorzy:
Choi, Bongkyoo
Ko, Sangbaek
Ostergren, Per-Olof
Powiązania:
https://bibliotekanauki.pl/articles/2177398.pdf
Data publikacji:
2015-03-26
Wydawca:
Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
Tematy:
epidemiological studies
Malmö
sensitivity
specificity
scoring methods
misclassification
Opis:
Objectives This study aims to test the validity of the IPD-Work Consortium approach for creating comparable job strain groups between the Job Content Questionnaire (JCQ) and the Demand-Control Questionnaire (DCQ). Material and Methods A random population sample (N = 682) of all middle-aged Malmö males and females was given a questionnaire with the 14-item JCQ and 11-item DCQ for the job control and job demands. The JCQ job control and job demands scores were calculated in 3 different ways: using the 14-item JCQ standard scale formulas (method 1); dropping 3 job control items and using the 11-item JCQ standard scale formulas with additional scale weights (method 2); and the approach of the IPD Group (method 3), dropping 3 job control items, but using the simple 11-item summation-based scale formulas. The high job strain was defined as a combination of high demands and low control. Results Between the 2 questionnaires, false negatives for the high job strain were much greater than false positives (37–49% vs. 7–13%). When the method 3 was applied, the sensitivity of the JCQ for the high job strain against the DCQ was lowest (0.51 vs. 0.60–0.63 when the methods 1 and 2 were applied), although the specificity was highest (0.93 vs. 0.87–0.89 when the methods 1 and 2 were applied). The prevalence of the high job strain with the JCQ (the method 3 was applied) was considerably lower (4–7%) than with the JCQ (the methods 1 and 2 were applied) and the DCQ. The number of congruent cases for the high job strain between the 2 questionnaires was smallest when the method 3 was applied. Conclusions The IPD-Work Consortium approach showed 2 major weaknesses to be used for epidemiological studies on the high job strain and health outcomes as compared to the standard JCQ methods: the greater misclassification of the high job strain and lower prevalence of the high job strain.
Źródło:
International Journal of Occupational Medicine and Environmental Health; 2015, 28, 2; 321-333
1232-1087
1896-494X
Pojawia się w:
International Journal of Occupational Medicine and Environmental Health
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of a Function of Misclassified Binary Data
Autorzy:
Al-Kandari, Noriah M.
Powiązania:
https://bibliotekanauki.pl/articles/973541.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
binary classification
double sampling
finite population sampling
misclassification
linkage error
sampling design
Opis:
We consider the problem of predicting a function of misclassified binary variables. We make an interesting observation that the naive predictor, which ignores the misclassification errors, is unbiased even if the total misclassification error is high as long as the probabilities of false positives and false negatives are identical. Other than this case, the bias of the naive predictor depends on the misclassification distribution and the magnitude of the bias can be high in certain cases. We correct the bias of the naive predictor using a double sampling idea where both inaccurate and accurate measurements are taken on the binary variable for all the units of a sample drawn from the original data using a probability sampling scheme. Using this additional information and design-based sample survey theory, we derive a biascorrected predictor. We examine the cases where the new bias-corrected predictors can also improve over the naive predictor in terms of mean square error (MSE).
Źródło:
Statistics in Transition new series; 2016, 17, 3; 429-448
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Polygraph Tests - Benefits and Challenges
Autorzy:
Babu Rajan, Panthayil
Powiązania:
https://bibliotekanauki.pl/articles/1037954.pdf
Data publikacji:
2019
Wydawca:
Academicus. International Scientific Journal publishing house
Tematy:
polygraph
autonomic responses
truthfulness
dishonesty
misclassification
Opis:
This research describes the working, benefits and challengers of polygraph tests. Polygraph tests are lie-detecting devices that help ascertain individuals’ honesty based on physiological indicators. The heart rate/blood pressure, respiration, and skin responses are the three indicators measured in the test to assess honest/deceitful behavior. The underlying assumption behind the working of polygraph tests is that the autonomic responses of dishonest individuals are distinctively different from those of honest people because the liars will be more nervous than truth tellers. Control Question Test (CQT), Guilty Knowledge Test (GKT) or Concealed Information Test (CIT) and Neuroscience-Based Advanced Polygraph Tests are the important types of polygraph tests used today. Polygraph tests are used to detect truthfulness of individuals in such important fields as crime investigation departments, national security agencies, and business and industry. However, accuracy of polygraph tests and ethical issues associated with the tests are highly debated.
Źródło:
Academicus International Scientific Journal; 2019, 19; 146-155
2079-3715
2309-1088
Pojawia się w:
Academicus International Scientific Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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