Assessing normality/kurtosis/skewness in SEM

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    When assessing the normality based on the skewness and kurtosis reading in SEM, which value do we actually refers to – the kurtosis value, or the critical ratio value.


    Literature indiates that value of 3.0 for skewness and 10 for kurtosis is acceptable (Kline, 2005).



    Jeremy Miles

    The value.  The value is a descriptor of how far from normality it is.  The critical ratio is used to get the p-value, which depends on the sample. So for a larger sample, the same degreed of skew (and hence the same problem) will have a larger critical ratio (which makes it seem like a worse problem.)


    Thanks Jeremy.

    diana k

    if you want to know about normality, skew is a VERY poor choice

    Kolmogorov – Smirnov, avaialble in most stats packages is much better, or try eyeballing a normal percentile plot, also avialble in eg SPSS.

    or just produce a simple box & whiskers diagram. if its non-normal and skewed then the 75% and 25% will not be equal distance from median, also 90% and 10%. if it is high kurtosis, but symmetric then outliers will show up.


    if the reason for non-normality test is to use t-test or ANOVA, then be aware that unequal variance is a wors problem than skew. use unequal variance form of tests





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