topic Re: Unusual Parameter Estimation in New SAS User

Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 06:35:42 GMT

Hello again.. I have an unusual parameter estimation for my variable.

Here's the output from SAS.

Does somebody know why is the estimation of parameter for variable DL3 is very high and so different from DL1 and DL2?

The interpretation of the model feels so wrong when the value is that high, because the value of DL3 shoud be around the value of DL1 and DL2.

Thankyou.

Re: Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 06:37:06 GMT

Here's the syntax I use for the analysis.

proc reg data = armaxvlp;                                                                                                                     
model Bill = Waktu DL1 DL2 DL3/influence;                                                                                                     
run;

Re: Unusual Parameter Estimation

PaigeMiller — Mon, 11 Mar 2019 11:56:17 GMT

@sasgiaz wrote:

Hello again.. I have an unusual parameter estimation for my variable.

Here's the output from SAS.

Does somebody know why is the estimation of parameter for variable DL3 is very high and so different from DL1 and DL2?

The interpretation of the model feels so wrong when the value is that high, because the value of DL3 shoud be around the value of DL1 and DL2.

Thankyou.

Since we don't know what DL1 DL2 and DL3 mean, and we don't have your data, its pretty much impossible for us (but not for you) to figure out why this is happening.

You can do some diagnostic checking yourself:

Make sure there are no extreme outliers in DL1 DL2 DL3
Actually PLOT the data (DL1 versus Y, etc.) and look at it
Check the influence diagnostics from PROC REG
Check the Variance Inflation Factors (option VIF) from PROC REG
Make sure there is no high correlation between DL1 DL2 DL3

Re: Unusual Parameter Estimation

Ksharp — Mon, 11 Mar 2019 12:19:43 GMT

I noticed you only have 36 obs , that is not enough for a Regression Model.

Also check Std of DL3 , that is way too high . This indicated you have a wrong model .

Re: Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 12:36:07 GMT

What do you think I should do?..

Re: Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 12:40:17 GMT

all DL is dummy variables...it contains so much zeros and some dummy proportions...it's a dummy variables for holiday variation. The VIF is fine..

Re: Unusual Parameter Estimation

Ksharp — Mon, 11 Mar 2019 12:45:36 GMT

1) collect more data

2) try other nonlinear effect ,like

model y=dl1 | dl2 | dl3 ;

try EFFECT statement to get spline / cubie nonlinear effect .

Re: Unusual Parameter Estimation

PaigeMiller — Mon, 11 Mar 2019 12:49:52 GMT

Before I would advise any of these, I would certainly check for outliers and the other problems I mentioned in my earlier message. If any of those problems are present, fitting a more complicated model will result in similar problems with the new model.

Re: Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 12:59:46 GMT

Here's the plot for each DL. If the outliers should be checked I think it's obvious for each DL to have extreme value because most of the variables valued zero since it is dummy variables

Re: Unusual Parameter Estimation

PaigeMiller — Mon, 11 Mar 2019 14:08:22 GMT

DL are dummy variables? Did not know that.

But to detect outliers you have to plot Y versis DL1, Y versus DL2, etc.

And then there were other recommendations I had as well, stated earlier, you need to check all of these.

Re: Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 15:30:11 GMT

Here's the plot Y (Bill) vs DL1, DL2, and DL3.

How can I tell about the outliers?

Here's the output for multicollinerity check.

The dummy variables don't have high correlation.

Lastly, I dont know which one is the influence diagnostics..

Re: Unusual Parameter Estimation

PaigeMiller — Mon, 11 Mar 2019 15:36:14 GMT

At this point, I suggest we take a major step backwards and re-examine the original problem. The whole idea of fitting a regression to this data makes little sense once you look at the plots.

Do these data look like they fit a straight line? Do these data look like they fit any line, straight or curved?

I would say, no they do not, and any effort to fit a linear regression here will result in poor fits and meaningless slopes.

Re: Unusual Parameter Estimation

sasgiaz — Mon, 11 Mar 2019 16:48:29 GMT

so you suggest to apply another model instead of regression? what model do you think will fit?

Re: Unusual Parameter Estimation

PaigeMiller — Mon, 11 Mar 2019 16:55:20 GMT

Again, you need to look at the data and see what potential models might fit. I don't see any patterns in this data. Do you?

When you have a huge percent of your data where x=0 and a very small percent of your data is where x>0, I don't think you can use a statistical model because the data is extremely unbalanced and there are no apparent patterns that can be modeled. I am not aware of any statistical modelling that will fit this data. In fact, it's hard to get any meaningful statistics in this extremely unbalanced case.

Re: Unusual Parameter Estimation

PaigeMiller — Mon, 11 Mar 2019 17:05:45 GMT

Adding:

Maybe a linear model with your y-variable and WAKTU as the x-variable makes sense, I don't know, I haven't seen the data. But modelling with DL1 DL2 DL3 isn't going to fit well, because there is no pattern.

Re: Unusual Parameter Estimation

Ksharp — Tue, 12 Mar 2019 12:08:20 GMT

Your DL1-DL3 's one level has 99% data ,so DL1-DL3 don't have any variance to explain Y .

My suggestion is deleting these DL1-DL3 on account of they are not right variable(no power) to predict Y .

Maybe @Rick_SAS @StatDave could give us some better advice .

Re: Unusual Parameter Estimation

sasgiaz — Thu, 21 Mar 2019 07:09:11 GMT

Hello I'm sorry for the late respond but I'm so thankful for your kind help and answer. Thankyou!

Re: Unusual Parameter Estimation

sasgiaz — Thu, 21 Mar 2019 07:25:01 GMT

Hi, I'm sorry for the late respond. It's ok i'm done with the anaysis. Thank you so much for your kind help and attention:)