tips:models_with_or_without_intercept
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tips:models_with_or_without_intercept [2019/06/30 11:43] – external edit 127.0.0.1 | tips:models_with_or_without_intercept [2021/02/12 15:53] – Wolfgang Viechtbauer | ||
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==== Model With Intercept ==== | ==== Model With Intercept ==== | ||
- | The dataset is called '' | + | The dataset is called '' |
<code rsplus> | <code rsplus> | ||
library(metafor) | library(metafor) | ||
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H_0: \mu_a = \mu_r = \mu_s = 0. | H_0: \mu_a = \mu_r = \mu_s = 0. | ||
$$ | $$ | ||
- | This test is clearly significant ($p = .0011), which indicates that we can reject the null hypothesis that the (average) log risk ratio is zero for all three methods of allocation. | + | This test is clearly significant ($p = .0011$), which indicates that we can reject the null hypothesis that the (average) log risk ratio is zero for all three methods of allocation. |
Again, we could use the '' | Again, we could use the '' | ||
Line 245: | Line 245: | ||
==== Parameterization ==== | ==== Parameterization ==== | ||
- | What the example above shows is that, whether we remove the intercept or not, we are essentially fitting the same model, but using a different [[wp> | + | What the example above shows is that, whether we remove the intercept or not, we are essentially fitting the same model, but using a different [[wp> |
==== Models with Continuous Moderators ==== | ==== Models with Continuous Moderators ==== | ||
Line 303: | Line 303: | ||
</ | </ | ||
- | When the model only includes continuous (i.e., numeric) predictors/ | + | When the model only includes continuous (i.e., numeric) predictors/ |
==== References ==== | ==== References ==== |
tips/models_with_or_without_intercept.txt · Last modified: 2022/08/03 11:34 by Wolfgang Viechtbauer