Consulta: subjectFacets:"Misclassification"
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Data/hora: 17/06/2024 02:50:18

Misclassification probability as obese or lean in hypercaloric and normocaloric diet
Provedor de dados: 48
Autores: NASCIMENTO,ANDRÉ F; SUGIZAKI,MÁRIO M; LEOPOLDO,ANDRÉ S; LIMA-LEOPOLDO,ANA P; NOGUEIRA,CÉLIA R; NOVELLI,ETHEL L. B; PADOVANI,CARLOS R; CICOGNA,ANTONIO C.
The aim of the present study was to determine the classification error probabilities, as lean or obese, in hypercaloric diet-induced obesity, which depends on the variable used to characterize animal obesity. In addition, the misclassification probabilities in animáis submitted to normocaloric diet were also evaluated. Male Wistar rats were randomly distributed into two groups: normal diet (ND; n=31; 3,5 Kcal/g) and hypercaloric diet (HD; n=31; 4,6 Kcal/g). The ND group received commercial Labina rat feed and HD animáis a cycle of five hypercaloric diets for a 14-week period. The variables analysed were body weight, body composition, body weight to length ratio, Lee Índex, body mass Índex and misclassification probability. A 5% significance level was used....
Tipo: Journal article
Palavras-chave: Diet; Diet-induced obesity; Hypercaloric diet; Misclassification; Rats.
Ano: 2008
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602008000300002

APPLICATION OF RECURSIVE PARTITIONING TO AGRICULTURAL CREDIT SCORING
Provedor de dados: 31
Autores: Novak,   Michael P.; LaDue,   Eddy L.
Recursive Partitioning Algorithm (RPA) is introduced as a technique for credit scoring analysis, which allows direct incorporation of misclassification costs.  This study corroborates nonagricultural credit studies, which indicate that RPA outperforms logistic regression based on within-sample observations.  However, validation based on more appropriate out-of-sample observations indicates that logistic regression is superior under some conditions.  Incorporation of misclassification costs can influence the creditworthiness decision.
Tipo: Journal Article
Palavras-chave: Finance; Credit scoring; Misclassification; Recursive partitioning algorithm; Agricultural Finance.
Ano: 1999
URL: http://purl.umn.edu/15129

A tool for deterministic and probabilistic sensitivity analysis of epidemiologic studies
Provedor de dados: 31
Autores: Orsini,   Nicola; Bellocco,   Rino; Bottai,   Matteo; Wolk,   Alicja; Greenland,   Sander.
Classification errors, selection bias, and uncontrolled confounders are likely to be present in most epidemiologic studies, but the uncertainty introduced by these types of biases is seldom quantified. The authors present a simple yet easy-to-use Stata command to adjust the relative risk for exposure misclassification, selection bias, and an unmeasured confounder. This command implements both deterministic and probabilistic sensitivity analysis. It allows the user to specify a variety of probability distributions for the bias parameters, which are used to simulate distributions for the bias-adjusted exposure–disease relative risk. We illustrate the command by applying it to a case–control study of occupational resin exposure and lung-cancer deaths. By...
Tipo: Article
Palavras-chave: Episens; Episensi; Sensitivity analysis; Unmeasured confounder; Misclassification; Bias; Epidemiology; Research Methods/ Statistical Methods.
Ano: 2008
URL: http://purl.umn.edu/120927