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Smoothed incidence rates by single year of age were calculated by fitting a generalised additive model with penalised regression splines to the counts (Wood, 2008).
Because each individual chicken was included in the data set many times, we corrected for repeated measures by fitting a generalised linear mixed model (GLMM procedure), nesting day within individual chicken in the random model.
A range of parameter values were combined in 864 different CRR scenarios, with 1000 random data sets generated for each, and harm rates were estimated and tested for change over time by fitting a generalised linear model with a Poisson response.
In order to assess whether this had an impact on our findings we performed sensitivity analysis in which hysterectomy frequencies were modelled by fitting a generalised linear model, assuming a Poisson distribution and a log link function, to the NSW Admitted Patient Data from 1991 to 2008.
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Graphical plots of regression analysis between crown defoliation severity and tree diversity were obtained with ggplot2 (Wickham 2009) package, fitting a generalised additive model.
In brief, this involved fitting a generalised linear model assuming a Poisson distribution and a log link function to the NSW Admitted Patient Data from 1991 to 2008.
Generalised estimating equations (GEE) were used to explore the relationship between speciality and referral scores by fitting a general linear model for the mean score that specified the within GP and within speciality correlation structure of the data.
Finally, the GAM is a generalisation of generalised linear models and imposes minimal restrictions on the underlying relationship between the independent variable and the dependent variable by fitting a suitable spline function; that is, a set of polynomials.
Specifically, we attempted to fit a generalised linear mixed effects model with a Gamma error distribution and a log-link function.
To provide a baseline for evaluating the implications of an MSFR, we first fitted a generalised single species functional response [13] to our data (equation (3)).
To test H2.3, (PEP is associated with fewer reports of syringe confiscation), we will fit a Generalised Poisson Regression Mixed Model, with the rate of syringe confiscation by police as an outcome variable.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com