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R/check_model.R

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#' inside the error bounds. See [`binned_residuals()`] for further details.
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#'
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#' @section Residuals for (Generalized) Linear Models:
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#' Plots that check the normality of residuals (Q-Q plot) or the homogeneity of
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#' variance use standardized Pearson's residuals for generalized linear models,
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#' and standardized residuals for linear models. The plots for the normality of
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#' residuals (with overlayed normal curve) and for the linearity assumption use
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#' the default residuals for `lm` and `glm` (which are deviance residuals for
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#' `glm`).
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#' Plots that check the homogeneity of variance use standardized Pearson's
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#' residuals for generalized linear models, and standardized residuals for
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#' linear models. The plots for the normality of residuals (with overlayed
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#' normal curve) and for the linearity assumption use the default residuals
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#' for `lm` and `glm` (which are deviance residuals for `glm`). The Q-Q plots
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#' use simulated residuals (see [`simulate_residuals()`]) for non-Gaussian
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#' models and standardized residuals for linear models.
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#'
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#' @section Troubleshooting:
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#' For models with many observations, or for more complex models in general,

R/check_zeroinflation.R

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#'
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#' @section Tests based on simulated residuals:
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#' For certain models, resp. model from certain families, tests are based on
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#' simulated residuals (see [`simulated_residual()`]). These are usually more
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#' simulated residuals (see [`simulate_residual()`]). These are usually more
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#' accurate for testing such models than the traditionally used Pearson residuals.
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#' However, when simulating from more complex models, such as mixed models or
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#' models with zero-inflation, there are several important considerations.

man/check_model.Rd

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man/check_overdispersion.Rd

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man/check_zeroinflation.Rd

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