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Jul 5, 2018 at 11:29 history closed kjetil b halvorsen
whuber regression
Duplicate of Transforming variables for multiple regression in R
Jul 5, 2018 at 10:49 review Close votes
Jul 5, 2018 at 11:29
Jul 5, 2018 at 10:26 history edited kjetil b halvorsen
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Feb 18, 2015 at 11:48 comment added user3096214 Conceptual regression model: Pulse1 (continuous)= Body Mass Index (continuous) + ModerateExercise (dummy coded) + HighExercise (dummy coded) + error. Research question: Is there a relationship between BMI, exercise level and pulse1? I need to conduct a linear regression. Just want to know what my fist step should be. Is it to check the distribution of each continuous variable and then transform if necessary. Then create scatter plots and then fit the regression line using the ENTER method in SPSS, as this is exploratory?
Feb 16, 2015 at 21:32 comment added Glen_b Where to begin? Without a model, how are you assessing normality? If you're just looking at the response variable (DV) on its own, there's no assumption about that. With multiple variables, it can be difficult to assess linearity without adjusting for the other variables. [If you're using the data to choose a model which you then want to apply inference to, you need to account for the effect of that.] -- broadly speaking you should worry most about getting the description of the mean right, but where possible the form of the model should be based on subject area knowledge.
Feb 16, 2015 at 21:26 comment added whuber These issues have been extremely well covered in other threads. Start by searching our site on obvious keywords like "transform regression normal". That often turns up useful stuff. In this case you might want to exclude "logistic".
Feb 16, 2015 at 21:04 history asked user3096214 CC BY-SA 3.0