Hi stat friends! Can I please get some feedback/a sense check on my statistical approach based on reviewer comments of a scientific paper I am submitting? Is there anything really dumb in here or anything crucial I'm missing out? Thank you all for your wonderful help!
Here is an excerpt from my statistical section:
All data were checked for normality (ShaprioWilk) and variance (Levene’s test). To test for (cattle) browsing effect on foliar biomass(of trees) within species, the averages were compared prior to and post the cattle trial. When data were not normally distributed and (i) had comparable variances a Mann Whitney test was used (Species 1, Species 2), (ii) did not have comparable variances a Mood’s Median test was used (Species 3) [21].
I recently got feedback on a manuscript I submitted. "In the statistical section, why log transformation were not done for normality and equal variance test before using Mann Whitney test/Mood's Median test?”
Here is my response, I've attached exploratory plots of the data for Species 1 (Levene's test P>0.05, i.e. variances between samples are not different):
Non parametric testing for Species 1 and Species 2:
(a) It was felt that the median was a more appropriate representation of the data than the mean due to outliers.
(b) The outliers and zerovalues were valid results and were included in the analysis.
(c) Despite being a weaker statistical test, the assumptions of the nonparametric tests were met and the results of testing represented the observed change.
Does this sound ok?
Here is an excerpt from my statistical section:
All data were checked for normality (ShaprioWilk) and variance (Levene’s test). To test for (cattle) browsing effect on foliar biomass(of trees) within species, the averages were compared prior to and post the cattle trial. When data were not normally distributed and (i) had comparable variances a Mann Whitney test was used (Species 1, Species 2), (ii) did not have comparable variances a Mood’s Median test was used (Species 3) [21].
I recently got feedback on a manuscript I submitted. "In the statistical section, why log transformation were not done for normality and equal variance test before using Mann Whitney test/Mood's Median test?”
Here is my response, I've attached exploratory plots of the data for Species 1 (Levene's test P>0.05, i.e. variances between samples are not different):
Non parametric testing for Species 1 and Species 2:
 The data chosen for non parametric testing demonstrated a strong ‘left skew’.
 The data contained a majority of ‘0’ values, as the cattle completely defoliated the majority of the trees.
 Exploratory tests were used as follows: The Shapiro Wilk considered the data to be nonnormally distributed and the Levene’s test was used to check for homogeneity of variances and found the variances were not different.
 The data met the assumptions of the MannWhitneyWilcoxon test (wilcox.test with continuity correction) which assumes (1) the samples come from distinct populations, (2) the samples do not effect one another and (3) the populations have similar shapes of distribution and similar variances.
 We did also conduct explorations into transformation of the leftskewed data using logarithmic and square root transformations. Neither transformation resulted in a Gaussian distribution. The square root transformation was the one which most closely resembled a Gaussian distribution, and a Welch two sample t test found a significant differences in the means the samples (P<0.01)
 In the case of Species 3 the same process as that described above was followed. The postbrowsing data contained a majority of ‘0’ values, as the cattle completely defoliated the majority of the trees. Transformation would have been of limited use
 The results of the Levene’s test were P<0.05 so the data were not homogenous and therefore a mood’s median test was used.
(a) It was felt that the median was a more appropriate representation of the data than the mean due to outliers.
(b) The outliers and zerovalues were valid results and were included in the analysis.
(c) Despite being a weaker statistical test, the assumptions of the nonparametric tests were met and the results of testing represented the observed change.
Does this sound ok?
Attachments

54.5 KB Views: 2

21.5 KB Views: 2