On Friday, May 18, 2007 at 9:20:01 PM UTC+5:30, Kurt wrote:

Kylie:

I tried your method and SPSS correctly weighted out the dummy case.
The crosstab table showed 60% agreement (the raters agreed on 3 out of
5 valid ratings) which is correct. But it calculated Kappa as .000,
which is definitely not correct.

My test data was set up as follows:

###

Rater1 Rater2 Weight
Item1 Y Y 1
Item2 N Y 1
Item3 Y Y 1
Item4 Y Y 1
Item5 N Y 1
Dummy N N .000000001

###

Any ideas?

Kurt

On May 16, 7:58 pm, klange <[email protected]> wrote:

On May 17, 1:21 am, Kurt <[email protected]> wrote:

I am trying to assess the level of agreement between two raters who
rated items as either Yes or No. This calls for Kappa. But if one
rater rated all items the same, SPSS sees this as a constant and
doesn't calculate Kappa.

For example, SPSS will not calculate Kappa for the following data, because Rater 2 rated everything a Yes.

Rater1 Rater2
Item1 Y Y
Item2 N Y
Item3 Y Y
Item4 Y Y
Item5 N Y

SPSS completes the crosstab (which shows that the raters agreed 60% of the time), but as for Kappa, it returns this note:

"No measures of association are computed for the crosstabulation of VARIABLE1 and VARIABLE2. At least one variable in each 2-way table
upon which measures of association are computed is a constant."

Is there anywhere to get around this? I can calculate Kappa by hand
with the above data; why doesn't SPSS?

Thanks.

Kurt

Hi Kurt,

Add one extra case to your file with the value of 'N' for Rater 2 (and
any value for Rater 1). Add a weighting variable that has a value of 1
for your real cases, and a very small value for this new dummy case
(eg, 0.00000001). Weight the file by the weighting variable (Data >
Weight cases), and then run the Crosstabs/Kappa.

The new case is enough for the Kappa to be calculated, but the
weighting means that it won't impact your results.

Cheers,
Kylie.- Hide quoted text -

- Show quoted text -

If there are two rater R1 & R2, then Can you tell me how to add third coloum for weight in SPSS as you did, can share your SPSS screenshot?
Your will be a very big hand for me. my email id : [email protected]

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On Thu, 2 Jul 2020 08:06:50 -0700 (PDT), [email protected] wrote:

On Friday, May 18, 2007 at 9:20:01 PM UTC+5:30, Kurt wrote:

Kylie:

I tried your method and SPSS correctly weighted out the dummy case.
The crosstab table showed 60% agreement (the raters agreed on 3 out of
5 valid ratings) which is correct. But it calculated Kappa as .000,
which is definitely not correct.

My test data was set up as follows:

< snip, details >

If there are two rater R1 & R2, then Can you tell me how to add third coloum for weight in SPSS as you did, can share your SPSS screenshot?
Your will be a very big hand for me. my email id : [email protected]

The original thread from 2007 is available from Google, https://groups.google.com/forum/#!topic/comp.soft-sys.stat.spss/ChdrpJTsvTk

and it give plenty of reason why you don't really want to
have a kappa reported when there is no variation.

Especially study my posts and the one of Ray Koopman.

--
Rich Ulrich

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On Thu, 02 Jul 2020 12:11:16 -0400, Rich Ulrich
<[email protected]> wrote:

On Thu, 2 Jul 2020 08:06:50 -0700 (PDT), [email protected] wrote:

On Friday, May 18, 2007 at 9:20:01 PM UTC+5:30, Kurt wrote:

Kylie:

I tried your method and SPSS correctly weighted out the dummy case.
The crosstab table showed 60% agreement (the raters agreed on 3 out of
5 valid ratings) which is correct. But it calculated Kappa as .000,
which is definitely not correct.

My test data was set up as follows:

< snip, details >

If there are two rater R1 & R2, then Can you tell me how to add third coloum for weight in SPSS as you did, can share your SPSS screenshot?
Your will be a very big hand for me. my email id : [email protected]

The original thread from 2007 is available from Google, >https://groups.google.com/forum/#!topic/comp.soft-sys.stat.spss/ChdrpJTsvTk

and it give plenty of reason why you don't really want to
have a kappa reported when there is no variation.

Especially study my posts and the one of Ray Koopman.

I will add to a point that I made in the original discussion.

The reader's problem arises because "agreement" is intuitively
sensible in usual circumstances, but it is nonsensical under
close examination when the marginal frequencies are extreme.

"Reliability" for a ratings of diagnosis logicallyy decomposes
into Sensitivity and Specificity -- picking out the Cases, and
picking out the Non-cases. Kappa is intended to combine
those measures, essentially. It looks at "performance above
chance." (For a 2x2 table, it is closely approximated by the
Pearson correlation.)

I gave a hypothetical table {90, 5; 5, 0} with a negative kappa.
90 5
5 0

One can arbitrarily label the rows and columns as starting with
Yes or with No. In one labeling there is 90% "agreement" as to
who is a case (cell A) , in the other case there is 0% "agreement"
(cell D).

When each of two raters are seeing 95% as Case, chance would
have them agree SOME time; so the 'agreement" of 0 is below
chance, and the kappa is negative.

--
Rich Ulrich

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