waltKMO: waltKMO
In cognopod/walter: Functions and Visualizations for Factor Analysis
Description
Usage
Arguments
Details
Value
Description
waltKMO is a function for calculating Kaiser-Meyer using the Kaiser & Rice (1974) algorithm.
Usage
1
waltKMO(x)
Arguments
x
a dataframe containing all of the columns to be included in an analysis.
Details
Kaiser and Rice (1974) categorized KMO values using the following subjective appraisals.
in the 0.90s marvelous
in the 0.80s meritorious
in the 0.70s middling
in the 0.60s mediocre
in the 0.50s miserable
below 0.50 unacceptable
Value
A list of components.
KMO
The overall measure of sampling adequacy.
MSA
Measures of sampling adequacy for each item.
cognopod/walter documentation built on May 20, 2019, 11:16 a.m.
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Description Usage Arguments Details Value
Description
waltKMO is a function for calculating Kaiser-Meyer using the Kaiser & Rice (1974) algorithm.
Usage
1 | waltKMO(x)
|
Arguments
x |
a dataframe containing all of the columns to be included in an analysis. |
Details
Kaiser and Rice (1974) categorized KMO values using the following subjective appraisals.
| in the 0.90s | marvelous |
| in the 0.80s | meritorious |
| in the 0.70s | middling |
| in the 0.60s | mediocre |
| in the 0.50s | miserable |
| below 0.50 | unacceptable |
Value
A list of components.
KMO |
The overall measure of sampling adequacy. |
MSA |
Measures of sampling adequacy for each item. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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