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From |
"William Buchanan" <william@williambuchanan.net> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: Multiple linear regression the right approach? |

Date |
Tue, 25 Jun 2013 10:48:16 -0700 |

Hi Simon, You could probably get a much better response if you provided some basic information about your data to the listserv (e.g., descriptive statistics, what the data are, etc...). If one of your independent variables is categorical it wouldn't have a scale that would be interpretable (e.g., if you coded Black = 3; White = 2; Asian = 1 it doesn't mean that Whites or Asians have less of a racial property and the numbers signify nothing); I assume that you meant that the variable is ordinal in nature (e.g., the numbers convey magnitude but are not necessarily proportional). Which variable do you assume is not linearly related to your dependent variable? Are your dependent variable and independent variables measured on similar scales (in terms of orders of magnitude)? What does the non-linear relationship appear to be (e.g., quadratic, cubic, quartic, something else, etc...)? It is difficult to provide any useful feedback without knowing more of these details and any feedback at this point could lead you to the same place. HTH, Billy -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Simon Hauburger Sent: Monday, June 24, 2013 11:47 AM To: statalist@hsphsun2.harvard.edu Subject: st: Multiple linear regression the right approach? Dear potential helpers, I have a problem figuring out the right regression for my model: - It has a interval dependent variable (costs in $) that looks normally distributed, but according to shapiro-wilk test isn't - a number of independent variables which are categorial (scale from 1-6) and interval (assets in $) My first guess was to use a multiple linear regression, but not all of the independent variables are linearly related to the dependent variable (tested with cprplot lowess), even after having tried the common transformation techniques (log, square...) Any reommendations for my next steps? Keep trying to transform the variables and use the multiple linear regression or try an alternative method? If so, which method could it be? Logistic regression? (Transformation of the dependent variable to a binary variable is possible) I am really confused, statistics will never become my best friend.... Thank you for your help! Best * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Multiple linear regression the right approach?***From:*Simon Hauburger <simonhauburger@gmail.com>

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