scholarly journals Parameter estimation and use of gamma interferon assay for the diagnosis of bovine tuberculosis in Brazil

2012 ◽  
Vol 32 (4) ◽  
pp. 279-283 ◽  
Author(s):  
Luciano B. Lopes ◽  
Telma M. Alves ◽  
Ana Paula R. Stynen ◽  
Pedro M.P.C. Mota ◽  
Rômulo C. Leite ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Multiple Testing ◽  
Latent Class ◽  
Latent Class Model ◽  
Tuberculin Test ◽  
Gamma Interferon ◽  
Kappa Statistics ◽  
Class Model ◽  
Parallel Testing ◽  
Serial Testing

This study aimed to evaluate the interference of tuberculin test on the gamma-interferon (INFg) assay, to estimate the sensitivity and specificity of the INFg assay in Brazilian conditions, and to simulate multiple testing using the comparative tuberculin test and the INFg assay. Three hundred-fifty cattle from two TB-free and two TB-infected herds were submitted to the comparative tuberculin test and the INFg assay. The comparative tuberculin test was performed using avian and bovine PPD. The INFg assay was performed by the BovigamTM kit (CSL Veterinary, Australia), according to the manufacturer's specifications. Sensitivity and specificity of the INFg assay were assessed by a Bayesian latent class model. These diagnostic parameters were also estimate for multiple testing. The results of INFg assay on D0 and D3 after the comparative tuberculin test were compared by the McNemar's test and kappa statistics. Results of mean optical density from INFg assay on both days were similar. Sensitivity and specificity of the INFg assay showed results varying (95% confidence intervals) from 72 to 100% and 74 to 100% respectively. Sensitivity of parallel testing was over 97.5%, while specificity of serial testing was over 99.7%. The INFg assay proved to be a very useful diagnostic method.

scholarly journals Investigational approach to adenoviral conjunctivitis: comparison of three diagnostic tests using a Bayesian latent class model

2018 ◽  
Vol 12 (01) ◽  
pp. 043-051 ◽  
Author(s):  
Raja Sundaramurthy ◽  
Rahul Dhodapkar ◽  
Subashini Kaliaperumal ◽  
Belgode Narasimha Harish
Keyword(s):  
Sequence Analysis ◽  
Multiplex Pcr ◽  
Sensitivity And Specificity ◽  
Latent Class ◽  
Latent Class Model ◽  
Hypervariable Region ◽  
Human Adenovirus ◽  
Hexon Gene ◽  
Class Model ◽  
Pcr Targeting

Introduction: Highly contagious adenoviral conjunctivitis represents 15-70% of all conjunctivitis worldwide. Human adenovirus (hAdV) serotypes 3,4,7,8,19 and 37 contributes to 89% of all adenoviral conjunctivitis. Accurate and rapid diagnosis of adenoviral infections at serotype level could prevent misdiagnosis, spread of disease, unnecessary antibiotic use and increased treatment costs. Methodology: Sixty-two suspected viral conjunctivitis cases were recruited from November2013-January2015. Swabs collected from inferior palpebral conjunctiva and processed for viral culture (Hep2 cell line), immunofluorescence assay (IFA) and polymerase chain reaction (PCR) (targeting hexon gene). Serotype 3,4,7,8,19 and 37 identification was carried out with an optimized multiplex-PCR (based on hypervariable region of hexon gene) and confirmed by sequence analysis. Bayesian Latent Class Model (LCM) analysis was used to compare sensitivity and specificity of three tests. Results: Adenovirus was detected in 54.8% (34/62) of cases by combination of all three methods. Culture was positive in 23/34 cases (67.6%). PCR and IFA detected adenovirus in 24 (70.5%) and 21 (61.7%) cases respectively. LCM analysis revealed, sensitivity and specificity of PCR, Culture and IFA was 77.8% and 92.4%; 72.2% and 90.8%; 67.6% and 92.9% respectively. Serotyping by multiplex-PCR showed, two cases each were hAdV3 and hAdV4, 18 hAdV8 and two remained unidentified. Results of Multiplex-PCR and sequence analysis showed 100% concordance Conclusion: LCM analysis revealed, PCR is the most appropriate method for identification. Multiplex-PCR is a simple and rapid method (serotypes identification within two days); owing its short turnaround time and accuracy, it can be used as a diagnostic tool for surveillance of adenoviral keratoconjunctivitis.

scholarly journals Customers’ Mode Choice Behaviors of Express Service Based on Latent Class Analysis and Logit Model

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Lian Lian ◽  
Shuo Zhang ◽  
Zhong Wang ◽  
Kai Liu ◽  
Lihuan Cao
Keyword(s):  
Logit Model ◽  
Choice Behavior ◽  
Latent Class ◽  
Latent Class Model ◽  
Policy Research ◽  
Multinomial Logit Model ◽  
Class Model ◽  
Taste Heterogeneity ◽  
Using Data ◽  
Service Choice

As the parcel delivery service is booming in China, the competition among express companies intensifies. This paper employed multinomial logit model (MNL) and latent class model (LCM) to investigate customers’ express service choice behavior, using data from a SP survey. The attributes and attribute levels that matter most to express customers are identified. Meanwhile, the customers are divided into two segments (penny pincher segment and high-end segment) characterized by their taste heterogeneity. The results indicate that the LCM performs statistically better than MNL in our sample. Therefore, more attention should be paid to the taste heterogeneity, especially for further academic and policy research in freight choice behavior.

scholarly journals A Comparison of Mixture Modeling Approaches in Latent Class Models With External Variables Under Small Samples

2017 ◽  
Vol 78 (6) ◽  
pp. 925-951 ◽  
Author(s):  
Unkyung No ◽  
Sehee Hong
Keyword(s):  
Sample Size ◽  
Latent Class ◽  
Latent Class Model ◽  
Mixture Modeling ◽  
Small Sample ◽  
Outcome Variable ◽  
Parameter Estimates ◽  
Class Model ◽  
Modeling Approaches ◽  
Distal Outcome

The purpose of the present study is to compare performances of mixture modeling approaches (i.e., one-step approach, three-step maximum-likelihood approach, three-step BCH approach, and LTB approach) based on diverse sample size conditions. To carry out this research, two simulation studies were conducted with two different models, a latent class model with three predictor variables and a latent class model with one distal outcome variable. For the simulation, data were generated under the conditions of different sample sizes (100, 200, 300, 500, 1,000), entropy (0.6, 0.7, 0.8, 0.9), and the variance of a distal outcome (homoscedasticity, heteroscedasticity). For evaluation criteria, parameter estimates bias, standard error bias, mean squared error, and coverage were used. Results demonstrate that the three-step approaches produced more stable and better estimations than the other approaches even with a small sample size of 100. This research differs from previous studies in the sense that various models were used to compare the approaches and smaller sample size conditions were used. Furthermore, the results supporting the superiority of the three-step approaches even in poorly manipulated conditions indicate the advantage of these approaches.

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