P.Mean >> Category >>  Analysis of means (ANOM) (created on 2007-06-18).

Analysis of means (ANOM) is an approach used in quality control circles to compare averages, proportions, or counts across several groups. Also see Category: Analysis of variance, Category: Control charts, and Category: Quality control. Other entries about accrual problems in clinical trials can be found in the analysis of means page at the StATS website.


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Karen Homa. Analysis of Means Used to Compare Providers' Referral Patterns. Quality Management in Health Care. 2007;16(3):256-264. Abstract: "Objectives: The objective of this study was to demonstrate through a case study how an analysis of means (ANOM) chart can be used to compare groups and to advocate the usefulness of this method in improvement work. Methods: The ANOM technique was used to compare referral rates among providers at the Dartmouth-Hitchcock Medical Center's Spine Center. The purpose was to see whether there were any differences across providers in referral rates to Behavioral Medicine services for patients who scored low on their mental health score and whether referral rates were any different among the patient characteristics. ANOM charts were also used to determine whether patient characteristics were different among the providers. Results: Six of the 17 providers had significantly different referral rates compared to the overall referral rate of 38%. Seven patients' characteristics had a significantly different referral rate compared to the system's rate. The additional ANOM charts used to compare providers relative to specific patient characteristics demonstrated several special causes and revealed characteristic referral patterns for some of the providers analyzed. Conclusion: The ANOM chart may be underutilized in health care improvement work. The ANOM procedure of analyzing patient characteristics to determine differences among providers could be explored in other patient populations and settings." [Accessed December 1, 2009]. Available at: http://journals.lww.com/qmhcjournal/pages/articleviewer.aspx?year=2007&issue=07000&article=00009&type=abstract.

Creative Commons License All of the material above this paragraph is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon. Anything below this paragraph represents material from my old website, StATS. Until recently (June 2012), this material was available through Children's Mercy Hospital, but is no longer available there. Although I do not hold clear copyright for this material, I am reproducing it here as a service. See my old website page for more details.


9. Stats: ANOM table for alpha=0.05, part 2 (April 21, 2007). Here's a table of critical values for analysis of means (ANOM) at an alpha level of 0.05. It is a continuation of the table Stats: ANOM table for alpha=0.05, part 1 (created 2007-03-04) and shows larger values of I.

8. Stats: What I'm working on right now (created 2007-03-18). There are several research projects where I am actively looking for collaborators. I thought I'd outline these topics briefly here.

7. Stats: Calculation of Analysis of Means limits (created 2007-03-06). This page shows some of the details for calculating an analysis of means (ANOM) chart.

6. Stats: Analysis of Means answers to "on your own" exercises (created 2007-03-06). On the web page Stats: Calculation of Analysis of Means limits (March 6, 2007) you were asked to calculate ANOM charts for two different data sets.

5. Stats: ANOM table for alpha=0.05, part 1 (created 2007-03-04). Here's a table of critical values for analysis of means (ANOM) at an alpha level of 0.05.

4. Stats: Analysis of Means calculations (created 2007-03-02). Analysis of Means (ANOM) are available for a wide range of data sets, and it is impossible to summarize all the applications of ANOM here. The goal on this web page is to illustrate a few of the calculations.

3. Stats: Team exercise to illustrate ANOM calculations (created 2007-02-28). I am in charge of a workshop for the American Society for Andrology for their 32nd Annual Conference in Tampa Florida. This society holds a laboratory workshop every year, and this year, it is being split into two workshops: Sperm Morphology -A Hands-On Workshop, from 8am to 11:30am, and Quality Control -A Hands-On Workshop, from 1:30pm to 4:30pm. I will be teaching the afternoon workshop along with Dr. Steven Schrader. Some brief details about both classes are on the web: a preliminary schedule, a flier in PDF format, and a brochure in PDF format.

2. Stats: When is a control chart not a control chart? (created 2007-02-06). I found a pair of data sets on the web that represent counts and where one goal of the data collection is to see if any of the individual counts differ from the overall average. They look quite similar and you might be tempted to analyze both of them using a control chart. But the second example is different in subtle, but important ways and it is better analyzed using an approach called Analysis of Means (ANOM).


1. Stats: Some resources for Analysis of Means (created 2006-06-30, updated 2007-02-01). One of the techniques recommended by Davis Balestracci when he visited CMH in June 2006 was Analysis of Means, which often is abbreviated ANOM. You can use ANOM much like a control chart, but it is applied when you have a collection of averages representing the performance of specific subgroups. The classic application is examining the performance of several different workers who are all performing a similar task. I tend to dislike examples like that because it implies that the root cause of most problems lies in the workers themselves. That's not really true, though, but even if it were, such a focus early on in a quality program would lead to a lot of resistance, defensiveness, and possibly even fudging the numbers. Still, ANOM is a useful tool that has a lot of profitable applications.

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