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Maximum likelihood incidence α of IS in Germany and 95% confidence bounds for the population models v0, v1, v2, v3 and v4 The corrected incidence α and the corresponding 95% confidence bands for the different population models v0, v1, v2, v3 and v4 are very similar (see Table 2).
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Tabulation of individual records into person years tables and Poisson regression analyses of person years at risk, with calculation of maximum likelihood estimates of incidence rate ratios (IRR) and likelihood ratio tests were performed by means of the EPICURE programme package (Preston et al, 1996).
Maximizing this term with regard to α will yield the maximum likelihood estimate for the true incidence α.
*Population data for 2006 provided by the German Federal Office for Statistics **The corrected incidence is estimated by a maximum likelihood approach (taking into account the underreporting) Uncorrected annual IS incidence α in Germany based on the ESPED data and corrected IS incidence estimated by a maximum likelihood approach which takes into account the underreporting.
We then introduce a methodology which yields a non-parametric maximum likelihood estimate of the age-specific incidence distribution based solely on cohort-of-cases data, possibly supplemented with a known birth rate.
The model, formulated using difference equations (Text S1, equations 1 4), was fitted using maximum likelihood estimation (Text S5) to the incidence and prevalence data from the HIV surveys conducted in Caió in 1990 , 1997and 2007, under an assumption of independence.
For fixed βT and ΩT, we can approximate the distributions of prevalence and incidence at the time of the incidence assays by using the maximum likelihood.
In their first paper, Ferguson et al. [4] used maximum likelihood methods to fit to the observed incidence time series, but did not attempt to fit to the spatio-temporal pattern of spread.
Therefore, we used a maximum likelihood approach for the estimation of the corrected incidence taking under-reporting into account.
In addition, the maximum likelihood approach used to estimate the corrected IS incidence α takes into account the empirical distribution of the reporting quota.
The maximum likelihood estimator of λ i is the unadjusted standardized incidence ratio (SIR), the ratio of observed to expected within each ED [ 27, 32].
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