1990
DOI: 10.1007/978-3-642-75398-5_2
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Mathematics and Statistics for Analyses in Epidemiology

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Cited by 61 publications
(38 citation statements)
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“…The standardised area under the disease progress curve (AUDPC) for each treatment was calculated by trapezoidal integration of the respective observation period. Using non-linear regression of STATISTICA software (StatSoft, Inc. 2001), the generalised beta function (Hau and Kranz 1990) and the monomolecular model (Campbell and Madden 1990) were respectively fitted to the data to describe effects of temperature and leaf wetness duration on AUDPC, lesion density, lesion size, and disease severity. The generalised beta function is described as Y = b 1 (T-b 2 ) b3 (b 4 -T) b5 , and the monomolecular model is Y = b 6 (1-b 7 exp(-b 8 M)).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The standardised area under the disease progress curve (AUDPC) for each treatment was calculated by trapezoidal integration of the respective observation period. Using non-linear regression of STATISTICA software (StatSoft, Inc. 2001), the generalised beta function (Hau and Kranz 1990) and the monomolecular model (Campbell and Madden 1990) were respectively fitted to the data to describe effects of temperature and leaf wetness duration on AUDPC, lesion density, lesion size, and disease severity. The generalised beta function is described as Y = b 1 (T-b 2 ) b3 (b 4 -T) b5 , and the monomolecular model is Y = b 6 (1-b 7 exp(-b 8 M)).…”
Section: Methodsmentioning
confidence: 99%
“…Estimated parameters are b 1 -b 8 ; minimum and maximum temperatures are b 2 and b 4 ; T is temperature (°C); M is leaf wetness duration (h); and Y is one of the specified disease variables (AUDPC, lesion density, lesion size, or disease severity). Combining the effect of temperature and leaf wetness duration allowed the fitting of a response surface of the disease variables, namely a monomolecular-beta function: (Hau and Kranz 1990).…”
Section: Methodsmentioning
confidence: 99%
“…Os dados obtidos foram submetidos à análise de variância (P<0,05), usando a transformação . Em função da temperatura, foi ajustado o modelo beta generalizado, y = b 1 ((xb 2 ) b4 )((b 3 -x) b5 ), descrito por Hau & Kranz (1990), onde y representa a produção de pseudotécios, x, a temperatura, b 2 e b 3 representam respectivamente, as temperaturas mínima e máxima, e b 1 b 4 b 5 são parâmetros sem significado biológico. Os resultados foram analisados utilizando o programa STATISTIC para Windons versão 6.0.…”
Section: Guignardia Citricarpaunclassified
“…The generalized β model was selected because it provided a good fit for all combinations of isolates and cultivars. The generalized β model (11) (p<0.05). Non-linear regression analysis was used to evaluate the relationship between the incubation and latent periods and the temperature.…”
Section: Discussionmentioning
confidence: 99%