Turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

- Home
- /
- Analytics
- /
- Forecasting
- /
- proc model dummies

Options

- RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Mute
- Printer Friendly Page

🔒 This topic is **solved** and **locked**.
Need further help from the community? Please
sign in and ask a **new** question.

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

Posted 04-03-2018 10:58 AM
(1943 views)

I am runnig proc model and when I add dummies in my regression the model converges but in the output T-values are **B.**

what does it mean and How I can solve that????

1 ACCEPTED SOLUTION

Accepted Solutions

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

thanks I find the solution. just eliminate the constant in the model.

13 REPLIES 13

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

this my model

disGDFF=a+a1*logage+a2*logTNA+a3*logMT+a4*EXP_RATIO+a5*turn+a6*logtnasq+a7*AG+a8*EI+a9*G+a10*LTG+a11*GI+a12*MC+a13*MRC+a14*SC+a15*MCG;

AG EI G LTG GI MC MRC SC MCG are style dummies variables. by line dummy will be 1 for one style for example G and 0 for others styles

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

That doesn't answer my questions.

@sasphd wrote:

this my model

disGDFF=a+a1*logage+a2*logTNA+a3*logMT+a4*EXP_RATIO+a5*turn+a6*logtnasq+a7*AG+a8*EI+a9*G+a10*LTG+a11*GI+a12*MC+a13*MRC+a14*SC+a15*MCG;

AG EI G LTG GI MC MRC SC MCG are style dummies variables. by line dummy will be 1 for one style for example G and 0 for others styles

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

so I did not understand your question ?? can you please explain what did you mean by levels

How did you create your dummy variables?

if the style = AG so AG=1 else AG=0

How did you create your dummy variables?

if the style = AG so AG=1 else AG=0

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

If you have a categorical variable, say Sex, it has two levels, F and M.

Using whatever method you used to create the dummy variables did you create one or two dummy variables?

@sasphd wrote:

so I did not understand your question ?? can you please explain what did you mean by levels

How did you create your dummy variables?

if the style = AG so AG=1 else AG=0

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

for each dummy variable is 1 or 0

and I have nine dummies variables

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

I can't see your data or code so I'm trying to make a generic example that we can both refer to, which is why I'm using SEX as the example.

If you had SASHELP.CLASS for example and wanted to include Sex in the model, which has 2 levels, F and M.

You would create N-1 dummy variables, where N is the number of levels.

So this means 1 dummy variable, such as Sex: 1 = Female, 0 = male.

I don't know what you did or how you created your variables (I have asked but you never answered the questions) so I'm assuming you created two dummy variables. Because of this, the dummies are linear combinations of each other so that there is redundant information. In this case, there cannot be an estimate for one of the dummy variables.

Good Luck.

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

Thanks you.

Just to give you an idea of my data

id EI G LTG GI MC MRC SC MCG

1 0 0 0 0 0 0 0 1

2 1 0 0 0 0 0 0 0

Just to give you an idea of my data

id EI G LTG GI MC MRC SC MCG

1 0 0 0 0 0 0 0 1

2 1 0 0 0 0 0 0 0

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

You need to answer the initial questions.

How many categories did you originally have before creating dummy variables?

Your Answer:

How many dummy variables did you created?

Your Answer:

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

How many categories did you originally have before creating dummy variables?

Your Answer: 9 categories

How many dummy variables did you created?

Your Answer: 9 categories

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

@sasphd wrote:

How many categories did you originally have before creating dummy variables?

Your Answer: 9 categories

How many dummy variables did you created?

Your Answer: 9 categories

You need 8, not 9. Because you can figure out the 9th from the other 8.

So you either get one that's reported as B, or exclude it from the analysis in the first place. This is known as your reference group, what all the other levels are compared to as the 'baseline' for example.

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content

thanks I find the solution. just eliminate the constant in the model.

**SAS Innovate 2025** is scheduled for May 6-9 in Orlando, FL. Sign up to be **first to learn** about the agenda and registration!

Multiple Linear Regression in SAS

Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.

Find more tutorials on the SAS Users YouTube channel.