| ... | @@ -26,7 +26,9 @@ When constructing a generalized linear model, three major decisions must be made |
... | @@ -26,7 +26,9 @@ When constructing a generalized linear model, three major decisions must be made |
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1. **Specifying the Random Component:**
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1. **Specifying the Random Component:**
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An appropriate probability distribution for the response variable must be chosen. This
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An appropriate probability distribution for the response variable must be chosen. This
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should be any member from the *natural exponential family* distributions:
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should be any member from the *natural exponential family* distributions. For the
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psychological and behavioral research the most important distributions are:
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- Continuous variables:
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- Continuous variables:
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* Normal
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* Normal
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* Gamma
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* Gamma
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| ... | @@ -35,6 +37,25 @@ When constructing a generalized linear model, three major decisions must be made |
... | @@ -35,6 +37,25 @@ When constructing a generalized linear model, three major decisions must be made |
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* Poisson
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* Poisson
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* Bernoulli
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* Bernoulli
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* Binomial
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* Binomial
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We should note that this distribution is not the *true* distribution of the population,
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but is a, approximation of the distribution of response variable. Each natural
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exponential family distribution can be parameterized by *natural parameter* <a
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href="https://www.codecogs.com/eqnedit.php?latex=\theta" target="_blank"><img
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src="https://latex.codecogs.com/svg.latex?\theta" title="\theta" /></a> and *dispersion
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parameter* <a href="https://www.codecogs.com/eqnedit.php?latex=\phi" target="_blank">
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<img src="https://latex.codecogs.com/svg.latex?\phi" title="\phi" /></a>. Parameter <a
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href="https://www.codecogs.com/eqnedit.php?latex=\theta" target="_blank"><img
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src="https://latex.codecogs.com/svg.latex?\theta" title="\theta" /></a> has information
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about the location of the distribution and in its basic form is a function of
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distribution mean <a href="https://www.codecogs.com/eqnedit.php?latex=\mu"
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target="_blank"><img src="https://latex.codecogs.com/svg.latex?\mu" title="\mu" /></a>.
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On the other hand, the variance of the distribution is a function of <a
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href="https://www.codecogs.com/eqnedit.php?latex=\mu" target="_blank"><img
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src="https://latex.codecogs.com/svg.latex?\mu" title="\mu" /></a> and <a
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href="https://www.codecogs.com/eqnedit.php?latex=\phi" target="_blank"><img
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src="https://latex.codecogs.com/svg.latex?\phi" title="\phi" /></a>.
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2. **Specifying the Systematic Component (Linear Predictor):**
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2. **Specifying the Systematic Component (Linear Predictor):**
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A linear combination of predictor variables should be constructed as the linear
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A linear combination of predictor variables should be constructed as the linear
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predictor of the model.
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predictor of the model.
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