A cross-sectional study was performed on pigs of the Emilia Romagna region (Italy). Sampling was stratified by farms (#54), with 75 samples selected within each randomly selected farm. In two farms only, 80 samples were collected. Qualitative coprological examinations were performed on individual faecal samples, and results entered in a working sheet together with data about animals (in particular categories) and indicators of farm management. Due to the great number of variables potentially confounding one-another and of possible interactions, in order to evaluate the risk of being parasitized the use of multivariate logistic regressions was preferred. The number of variables was reduced and/or summary variables created before analysis, in order to avoid variables with missing values and because too many information had been collected in relation to the number of observation (Noordhuizen JPTM et al, 1997, Application of quantitative methods in veterinary epidemiology, Wageningen Pers, The Netherlands. Dohoo I et al, 2003, Veterinary epidemiologic research, AVC Inc, Canada).
Stancampiano L., Poglayen G., Marchesi B., Bianchi M., Gradilone L., Di Bello F. (2008). Risk analysis for pig gastrointestinal parasites.
Risk analysis for pig gastrointestinal parasites
STANCAMPIANO, LAURA;POGLAYEN, GIOVANNI;MARCHESI, BARBARA;
2008
Abstract
A cross-sectional study was performed on pigs of the Emilia Romagna region (Italy). Sampling was stratified by farms (#54), with 75 samples selected within each randomly selected farm. In two farms only, 80 samples were collected. Qualitative coprological examinations were performed on individual faecal samples, and results entered in a working sheet together with data about animals (in particular categories) and indicators of farm management. Due to the great number of variables potentially confounding one-another and of possible interactions, in order to evaluate the risk of being parasitized the use of multivariate logistic regressions was preferred. The number of variables was reduced and/or summary variables created before analysis, in order to avoid variables with missing values and because too many information had been collected in relation to the number of observation (Noordhuizen JPTM et al, 1997, Application of quantitative methods in veterinary epidemiology, Wageningen Pers, The Netherlands. Dohoo I et al, 2003, Veterinary epidemiologic research, AVC Inc, Canada).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.