Hi all

I have a question pertaining to Attribute MSA Study using Kappa

In attribute study; a "1" represent an acceptable decision and a "0" represent an unacceptable decision.

I found that if there is a lot of "1" (say almost 90% )between Appraisers and very little "0"; the calculated kappa value is very low. Probability less than 10%.

Can any one please help to explain why Kappa value is low when there is a alot of "1" decision and very little "o" decision.

Thanks in advance

KT:read:

Do you mean the study in the MSA manual?
In this case the kappa value is a lot higher than 10%.

In case you have made your own study it would be better to attach your data or your study here so people in the cove can evaluate.

Best regards,

Antoine

yes, please attach your data. without it, I can't tell what is happening to you...

Hi, :bigwave:

From my understanding, Kappa is to determine on the agreement level of decisions between appraisers. It has nothing / little to do with the "1" and "0" decision. When the is many mismatch decision between appraisers, your kappa tends to be low. Kappa close to 1 showing there is very strong agreement between appraisers (BUT not necessary right decision).

Please right me if I'm wrong.:rolleyes:

Hi guys,

When we get kappa = 1, it means it is perfect agreement. When we get kappa = 0, the agreement is the same as would be expected by chance. The higher the value of kappa, the stronger the agreement. Negative values occur when agreement is weaker than expected by chance, but this rarely happens. Depending on the application, kappa less than 0.7 indicates that the measurement system needs improvement. kappa values greater than 0.9 are considered excellent.:biglaugh:

Actually Kappa can be used for
1. ability to detect truth for each 'inspector'
2. within inspector repeatability and
3. between inspector reproducibility (or what some would term "agreement")

I use it for all 3 reasons on a regular basis.

For 1. you need a set of known standards, acceptable, marginal nad rejectable. you have the inspector inspect the set under normal inspection conditions. Then calculate Kappa with the known state as one of the "judges results" This test can be modified based on what you actually want to measure: if you are only testing the inspector's inate ability to make the correct call (given the appropriate training), you can use a sample set with any proportion of good marginal and rejectable parts. If you are conserned with their ability to make the correct call under typical inspection conditions (your real world) you need to have a sample set that is proportional to the current occurence rates of good, marginal and rejectable parts adn you must have the inspector inspect the set at the speed at whihc they woudl normlaly have and wiht the same lighting, magnification, etc.

2. You can - and should - then test the same inpsector with the same set of samples again (presented in a different order) some time later - a couple of days or weeks later. Then calcualte the Kappa wiht the judges resutls being the first time and the second time: this gives you repeatability of the inspector.

3. repeat the above 2 across inspectors and use one set of resutls from each inspector (typically their first results to minimize learning bias) and you have reproducibility....

:topic:

Hi, I am just starting to use the Attribute MSA method in my company.

According to MSA 3rd Edition Manual : Cross-Tab Method, page 128, the number of samples set to be 50, with 3 appraisers and 3 trials.

The question is, can we have smaller number of sample, operator and trial to get the same effectiveness of Attribute MSA? If yes, how small can we go?

There is some concerns from the users that the number of Sample (50) is hard to get and time consuming.:nope:

Very much appreciate for any feedback.:thanx:

Attribute data requires a much greater sample size than variable data. For attributes, 50 should be considered a minimum. Smaller sample sizes will greatly increase the uncertainty of the results.

on the other hand it isn't necessary to have 3 trials...that's really overkill. In fact in the literature I've never seen 3 trials recommended. I've done - or managed - hundreds of Kappa studies, never done 3 trials and had great success with the method.

The sample size that is needed is dependent on what you are trying to do - review the existing threads here on Kappa for more info.

I've successfully used sample sizes ranging from 8 to 500...depends on your intent.

Attribute Studies used to be carried out using only 20 parts. However if you need to meet the TS16949 standard you will need to follow the MSA 3rd edition Manual and use 50 parts.

You should choose your parts carefully so that about 50% are non-conforming. The study where Kappa values are low may have too few non-conforming parts.

Unofficially, our consultant will say that the move to 50 parts has not been beneficial because the attribute studies become hard work and costly so not as many are carried out.
Regards
Celia

Attribute Studies used to be carried out using only 20 parts. However if you need to meet the TS16949 standard you will need to follow the MSA 3rd edition Manual and use 50 parts.

You should choose your parts carefully so that about 50% are non-conforming. The study where Kappa values are low may have too few non-conforming parts.

Unofficially, our consultant will say that the move to 50 parts has not been beneficial because the attribute studies become hard work and costly so not as many are carried out.
Regards
Celia

If all inspectors make the correct call each time then the score will be a 1; low kappa scores cannot be achieved simply by the inclusion of 'too few defects'. If there are no defects and the 'inspectors' call each of the good parts good then the Kappa score will be 1. (unless you are doign the math wrong or have input an incorrect formula)

If the inspectors don't make the correct call each time; the more incorrect calls the lower the score.

If the inspectors make perfectly incorrect or opposite calls each time the score will be -1.

The choice of how many defective parts to include depends on the intent of the study. typical use of the Kappa is to evaluate the inspector's ability to detect good parts and bad parts accurately under normal inspection conditions. In this case the percentage of defects (in total and by mix of defect types and marginality) should be representative of the current defect mix. This often requires sample sizes larger than 50 for production operations.

Good evening everyone. I am trying to learn how to use the MSA tool and complete an attribute gauge R and R on environmental compliance. I want evaluate the variance between several inspectors who are evaluating non-compliance of air pollutants. This test is more of a go-no go test, because the inspectors are been certified to a documented EPA standard and they just go out and evaluate non-compliance in the real world. Based on their certification and evalualtions of several criteria, they determine if a party exceeded the allowable standard. I wanted to use three inspectors, doing three repetitions, of three different samples. I was going to randomize the samples to eliminate bias. Am I on the right tract? Do I have enough sampling to accurately predict any issues. Thanks.

Can you tell us more about the test. Do they get an actual measurement then make a Pass/Fail decision, or does the measurement device simply read pass/fail?