R Is Not So Hard! A Tutorial, Part 4 (repost)

The following is not a Stats Make Me Cry original, but rather something I came across and found very useful. The article demonstrates how to examine non-linear effects (e.g. quadratic effects) using a regression model in R. If you are interested in the topic, please read the preview and follow the link that follows to the original site.

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Part 3 we used the lm() command to perform least squares regressions. In Part 4 we will look at more advanced aspects of regression models and see what R has to offer. One way of checking for non-linearity in your data is to fit a polynomial model and check whether the polynomial model fits the data better than a linear model. Or you may wish to fit a quadratic or higher model because you have reason to believe that the relationship between the variables is inherently polynomial in nature.

Let’s see how to fit a quadratic model in R...
Read the rest of R Is Not So Hard! A Tutorial, Part 4 here…

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Comments

[shalini]

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