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02-16-2017 09:12 PM

Hi,

I have a regression coefficient (y=1.11*x) of a regression model: KM % = 1.11*TEMR. In another independent data set say Set A, I have TEMR readings from the same instrument as well as KM% of 120 samples. Now if in the Set A, I first multiple TEMRx1.11 to get a variable say TEMR_modified and then like to test whether TEMR_modified would be any different from the KM% of the Set A?

What would be my options, please?

I first thought of treating TEMR_modified and Km% (both have N120) as two groups and run a two sample ttest, but don’t know if it would be valid (as I notice some occasional variation in both groups for respective readings).

Please, advise and if possible with a sas code, thank you all

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02-16-2017 10:29 PM

You can check that your new data supports (does not disagree with) the hypothesis that TEMR = 1.11 KM with proc REG:

```
proc reg data=A;
model TEMR = KM / noint;
test KM = 1.11;
run;
```

PG

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02-16-2017 11:26 PM

Hi,

Thank you very much for your suggestion. I ran the code "test = km 1.11" the particular SAS Output is:

Test 1 Results for Dependent Variable KM Source DF Mean

Square F Value Pr > F Numerator Denominator

Square F Value Pr > F Numerator Denominator

1 | 20.14595 | 0.33 | 0.5661 |

237 | 61.00256 |

I guess the default null hypothesis for the test=1.11 would be that the "new regression model's coefficient (TEMR=KM)" is no different than 1.11?

So, what about the question I asked in my original post, how to test that "TEMR_modified is no different than KM%". Or the above test is sufficient? please. Thank you again

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02-16-2017 11:58 PM

A 2 sample test might not have much power, depending on the range covered by km.

You could run a paired t-test of temr_modified and km. Or simply run proc univariate on diff = temr_modified - km.

If you have the original data that yielded the regression slope estimate of 1.11, you could also test that the original data and the new data yield the same slope.

PG

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02-17-2017 12:35 AM

Hi, thanks for the reply.

I am tempted to do the proc univariate on the diff (is it the simple subtraction of the two, right?, no squaring of the mean diff etc!!!!).

Your suggestions are appreciated.

Thanks again

I am tempted to do the proc univariate on the diff (is it the simple subtraction of the two, right?, no squaring of the mean diff etc!!!!).

Your suggestions are appreciated.

Thanks again