Solved: How can I run the test of homogeneity of variance (Levene's test)?

Reinaldo · May 3, 2018 11:25 AM

Hi,

How can I run the Levene's test in JMP?

Thank you.

~Rei

Mark_Bailey · May 3, 2018 12:19 PM

You have several ways to compare the variance in the Oneway platform. In addition to the way that Jeff showed, you can select Unequal Variances command and get this report:

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gzmorgan0 · May 4, 2018 06:16 AM

Reinaldo,

When there are complex effects, I typically recommend finding delta, the difference of the measured response minus the mean of fixed effects and time. To visualize these effects, create a column Mean Effect using the formula,

Col Mean( :Y, :Treatment, :Time )

Then create the column delta, Y - Mean effect. Next call up the Variability chart and plot Y, Delta and Mean Effect by Treatment, Time, etc. This provides a visual representation of the variability. Next combine columns representing the effects, call the new column Effects. Now perform a Oneway Analysis of Variance and test for Unequal Variances.

Many significance tests, especially for small sample group sizes or very large group sizes, might not flag or over flag. If there are at least 5 to 10 per group, look at the ratio of the max stdev to the min stdev and if the ratio is more than 3 then it is showing unequal variance with 11-20 if the ratio is more than 2 and no outliers, then varainces are likely unequal.

JMP has a rich repeated measures example data table Cholesterol Stacked.jmp. I modified it per these suggestions and added two scripts prefixed by gzm: gzm - Variability and gzm - Oneway. This study is looking at the effects of two (A and B) cholesterol lowering drugs vs. a control and a placebo. See attached file. Note the Levene's test in the report.

As you might expect those getting an effective treatment will have more variation than those that are not (a person with higher cholesterol to begin with might have bigger drop, and drugs do have the same effect on all).

The cholesterol data is also used for a Manova analysis with tests for unequal covariance (sphericity tests).

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gzmorgan0 · May 4, 2018 12:10 PM

To make the combined columns uncheck Indicators and multiple response.

From the attached scripts you should look at the data. From the Cholesterol Stacked data the variance is much larger for May and June for :Treatments levels A and B. Also I look for equal variances for the first time period. For a repeated measures, if one group's variance is much larger (or smaller) than the other groups' variance, this could be an indication of bias in the groups.

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Jeff_Perkinson · May 3, 2018 11:57 AM

A search of the JMP documentation online lead me to this page which shows that Levene's test is in the Analysis of Means (ANOM) section of Fit Y by X.

-Jeff

Reinaldo · May 3, 2018 12:07 PM

Hi @Jeff_Perkinson

Thank you for your post. In general, the result of homogeneity of variance (Levene's test) is given by F-ratio, p-value. So, how can I interpret ANOM to provide that F-ratio, p-value, please?

Thank you.

~Rei

Mark_Bailey · May 3, 2018 12:19 PM

You have several ways to compare the variance in the Oneway platform. In addition to the way that Jeff showed, you can select Unequal Variances command and get this report:

Reinaldo · May 3, 2018 12:27 PM

Thank you, Mark! Ah, I need to select Unequal Variances command to get F-ratio. Great! :)

~Rei

Reinaldo · May 3, 2018 12:30 PM

Please, @Mark_Bailey, just an additional question for this topic: in case I run a repeated-measures design, should I perform my outcome Weight By timepoint to test the homogeneity of variance?

Thank you.

~Rei

Mark_Bailey · May 3, 2018 12:40 PM

The homogeniety tests are availabe lin Oneway, not the other platforms that you would use for a repeated measures analysis.

Reinaldo · May 3, 2018 12:46 PM

Please, do you think it is correct to perform the outcome Weight By Timepoint using Oneway Analysis?

In this case, the variance of that outcome Weight will be shown across the timepoints. Does it make sense?

~Rei

Mark_Bailey · May 3, 2018 12:53 PM

I do not know the design of your study. I only know that the response is measured repeatedly over time

One way is not appropriate. You can examine the residuals from the repeated measures analysis to evaluate homogeneity.

Reinaldo · May 3, 2018 12:59 PM

Please, may you give me more information how to evaluate the homogeneity of variance using those residuals which are shown in the Fit Model?

Thank you, Mark!

~Rei

How can I run the test of homogeneity of variance (Levene's test)?

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Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?

Re: How can I run the test of homogeneity of variance (Levene's test)?