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I am comparing length of stay after laparoscopic and open appendectomy in over 160000 patients. LOS is typically a skewed variable so I use the median and interquartile range and ranksum test to describe the result, which is 2, IQR 2-3 and 2, IQR 2-4, p<0.0001. So there is a highly significant difference but it does not show that well in the median and IQR.

The difference in length of stay is very small. This finding is a negative finding but still interesting as it goes against what most people think about LOS after laparoscopic appendectomy. That is why I want to report on the difference in LOS which is not evident if I only report median and IQR with p-value.

The arithmetic mean (3.1 vs 2.8 and a difference of 0.3 days) is not recommended as the distribution is skewed. I wonder if any other measure could be used like, geometric mean (2.5 vs 2.3, difference 0.2 days) or harmonic mean (2.1 vs 1.9 days, difference 0.2 days)? When can I use geometric mean or harmonic mean?

I am inclined to use the harmonic mean which comes closest to the median and gives a difference of 0.2 days. Is this incorrect?

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You can use quantile regression and examine the association between surgical procedure and different quantiles of your outcome variable's distribution (length of stay). If some observations are censored, you can use Laplace regression instead (stats.stackexchange.com/a/27350/9253). –  boscovich Feb 20 '13 at 19:45
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Incidentally - with such a large sample size, even trivial differences in distribution will show up as statistically significant. You should focus on what matters in practical terms. –  Glen_b Feb 21 '13 at 0:32
    
Thanks for input. It is correct that I should focus on what matters in practical term. This finding is a negative finding but still interesting as it goes against what most people think about LOS after laparoscopic appendectomy. That is why I want to report on the difference in LOS which is not evident if I only report median and IQR with p-value (2, IQR 2-3 vs 2, IQR 2-4 days, p<0.0001). I am inclined to use the harmonic mean which comes closest to the median and gives a difference of 0.2 days. Is this incorrect? For multivariable models I will use Poisson-regression to adjust for covariates. –  Roland Feb 21 '13 at 7:41
    
Rolland, please complete the form at stats.stackexchange.com/help/user-merge to merge your multiple accounts: that will enable you to edit this question yourself. (It would be a mistake for any community member to approve the attempted edit because we have no way actually to verify the two accounts belong to you; that's why you need to do the merge.) –  whuber Feb 21 '13 at 8:33

3 Answers 3

If you want to describe the difference in distribution, perhaps something like a Q-Q plot, or a pair of kernel densities would be common tools, though I assume you have quite discrete looking distributions, in which case that may make something like a pair of barcharts/histograms or a pair of ECDFs better (if possible on a single display)

If you do go with looking at the difference in ECDF, the two-sample Kolmogorov-Smirnov statistic would be the ideal "measure" of significance to go with that, since it's based on the biggest (vertical) difference in ECDF.

If you compare barplots(/histograms) for a discrete distribution, you might like to look at the kinds of measures of discrepancy indicated by smooth tests of goodness of fit (Neyman-Barton type tests), but where the statistic is adapted to two samples. This would in effect correspond to partitioning a chi-square into components associated with orthogonal polynomials, the first of which would correspond to location (a linear term), the second to variance (a quadratic term), and so on (typically you'd look out to order 4 or 6). Books and numerous articles by Rayner and Best (and some others) cover some of that territory.

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What I want is just to enumerate the difference - to use some point estimate that show the difference. The median is the same, the arithmetic mean is not recommended as the distribution is skewed. Is it good standard to use the harmonic mean for this case? Or should I use another measure? –  Roland Feb 21 '13 at 0:25
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There are many ways that two distributions can differ. If you choose one measure, you may find no difference on that measure even if they still differ quite a bit. I'm in favor of using a single measure, if it captures what you need it to. The question is - will it? Something like the two-sample K-S picks up general differences. The partitions of the chi-square pick up general differences more weakly overall but let you choose a subset to focus on (notionally related to low order moments). If you have a specific measure you're confident will capture the differences you should use that. –  Glen_b Feb 21 '13 at 0:27

The same question has been discussed on the Google-group Medstats.

It was suggested that the arithmetic mean should be used as this is a more useful measure for planners. A difference in LOS of 0.3 days can be important for planning of health services and cost. Geometric and harmonic mean were dismissed as not correct to use in this situation.

Different approaches was proposed for modelling using quantile or Cox-regression.

I proposed poisson regression but ended up with negative binomial regression as the data showed evidence of overdispersion. This allowed me to compare the unadjusted difference of 0.3 days with difference after adjusting for age, sex, perforated appendicitis and period, which came down to a difference of only 0.05 days between the two surgical methods. This is important findings (although negative) as it goes against the common thinking about the advantages of laparoscopic appendectomy

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Like @Andrea , I like the idea of quantile regression as it seems to get at what you want.

If you really need a mean for each then, rather than the geometric or harmonic mean, I would suggest a trimmed or Winsorized mean. I find it strange that these are not used more. However, I would also think that % in hospital after X days would be useful and informative.

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