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From |
Emma <rmhaemh@ucl.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: inter and intra rater |

Date |
Mon, 22 Sep 2003 16:47:54 +0100 |

Dear Nick, (and statalist)

Many thanks for your prompt response to my initial question.

Earlier I sent the question below to statalist, but somewhat confusingly I only sent a subset of the data for the small disease group, below is the data for the entire set. where rater is the individual who took the measure, 6 individuals, subject 1 had small disease, subject 2 had moderate disease and subject 3 had large disease. and repeats 1 and 2 were the two repeated measurements taken by the raters.

ratersubject 1subject 1subject 2subject 2subject 3subject 3

repeat1repeat2repeat1repeat2repeat1repeat2

JT22.522.535.5356867.5

KD22.522.536.535.567.568.5

WD22.522.536.536.56768

NC222335.5366767

RP22.52236.536.56868.5

ES21.52336356867.5

I wondered if anyone has any suggestions to look at the three subjects together, whilst checking for inter rater and intra rater reliability,

Kindest regards and thanks,

Emma

At 16:18 22/09/03 +0100, you wrote:

Emma > I wonder if someone could help me with the following, I am > looking to > calculate intra rater and inter rater correlations on the > following data > set. A continuous variable has been measured by 6 trainees on three > different subjects (the three subjects have differing > degrees of disease: > small, moderate and large). All 6 trainees repeated the > measurements on > the three subjects on two separate occasions. > > I have applied ICC as a measure for the agreement between > the 6 raters; > however STATA outputs 0* for the ICC whereas the data > appears to show a > reasonable agreement in measures between raters: > > rater time1 time2 > JT 22.5 22.5 > KD 22.5 22.5 > WD 22.5 22.5 > NC 22 23 > RP 22.5 22 > ES 21.5 23 > > > . loneway var1 rater > > One-way Analysis of Variance for var1: measure2 > > Number of > obs = 12 > R-squared = 0.0870 > > Source SS df MS > F Prob > F > ------------------------------------------------------------ > ------------- > Between rater .16666667 5 .03333333 > 0.11 0.9845 > Within rater 1.75 6 .29166667 > ------------------------------------------------------------ > ------------- > Total 1.9166667 11 .17424242 > > Intraclass Asy. > correlation S.E. [95% Conf. Interval] > ------------------------------------------------ > 0.00000* 0.42817 0.00000 0.83921 > > Estimated SD of rater effect . > Estimated SD within rater .5400617 > Est. reliability of a rater mean 0.00000* > (evaluated at n=2.00) > > (*) Truncated at zero. > > > Also I wondered what measure I should use to consider the > agreement between > the repeat measures (should this be ICC also, and if so how > should the data > be set up, apologies to ask a basic question). Finally, is > there anyway to > consider the three subjects data together, i.e to combine > the info for the > small, moderate and large. One comment only, as I am mostly in the dark here: it is not clear to me how the subset of data you give is related to the analysis you report or to the problem you describe. Nevertheless, focusing on that subset alone, although the "agreement" between raters is close in the sense that all ratings are 21.5-23, which presumably is some small fraction of the possible range, the correlation (classic sense) is nevertheless strong and _negative_. However, another way of thinking about it is that your data points may collectively be one big blob. I guess wildly that this is consistent with small ICC. Nick n.j.cox@durham.ac.uk * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: inter and intra rater***From:*Emma <rmhaemh@ucl.ac.uk>

**st: RE: inter and intra rater***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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