BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
Shivi82
Quartz | Level 8

Hi All, Good Morning.

 

In a linear regression model that i am working on i have log transformed dependent variable due to data being skewed so below is the output from the model (Some of the values are mocked up with artificial var names):

 

Model

                       Parameter Estimate   Standard Error    Significance Value (P)

Intercept         7.346                                0.12                    .000

Carat              1.392                                .009                    .000

V GOOD        -.211                                 .016                    .000

GOOD           -.134                                 .013                     .000

Carat_I           -0.44                                .009                     .000

 

Here as the Dep var is log transformed we need to measure and interpret the coefficient in terms of percent change. So my question is while keeping var Carat as controlled which is most significant variable.

As per the estimates value it should be Good as it has a better slope value, however 

 

 the regression equation = 7.346-0.211 = 7.135 (with  V Good var)

 the regression equation = 7.346-0.134 = 7.212 (with Good var)

This has lead to some confusion. request you to please let me know if i am ok interpreting the results.

 

Regards, Shivi

 

 

 

 

1 ACCEPTED SOLUTION

Accepted Solutions
pearsoninst
Pyrite | Level 9
I am trying to answer without see all the parameters .You confusion is why V Good var is less then Good var . I belive it is because of the Std Error.You have classified VGV and GV due to some assumption or result , if those assumption or test are correct you are Good.

View solution in original post

3 REPLIES 3
pearsoninst
Pyrite | Level 9
I am trying to answer without see all the parameters .You confusion is why V Good var is less then Good var . I belive it is because of the Std Error.You have classified VGV and GV due to some assumption or result , if those assumption or test are correct you are Good.
Shivi82
Quartz | Level 8

Thank you, yes i have checked all the assumptions and they are true. 

However if you check the regression equation the variable Good has better value then V Good and that is what is confusing here. 

Shivi82
Quartz | Level 8

Please ignore the below question of "However if you check the regression equation the variable Good has better value then V Good and that is what is confusing here"

 

After looking carefully i can relate why good will be than Vgood because these var are impacting the outcome negatively and good is impacting more than v good.

 

Sometimes you tend to get confused when you work closely with the people who are either new or are only masters on books.

 

Thanks for the community for the help.

sas-innovate-2024.png

Don't miss out on SAS Innovate - Register now for the FREE Livestream!

Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.

 

Register now!

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 3 replies
  • 977 views
  • 0 likes
  • 2 in conversation