== Kruskal-Wallis, histology grade ==

	Kruskal-Wallis rank sum test

data:  grade by dose
Kruskal-Wallis chi-squared = 13.705, df = 2, p-value = 0.001057

== Dunn (Holm), rstatix ==
    .y.  group1 group2 n1 n2 statistic            p        p.adj p.adj.signif
1 grade vehicle    low  8  8  1.393473 0.1634766951 0.1634766951           ns
2 grade vehicle   high  8  8  3.667035 0.0002453791 0.0007361372          ***
3 grade     low   high  8  8  2.273562 0.0229923465 0.0459846929            *
== Approximate permutation p (coin, 100000 resamples, seed 1) ==

	Approximative Kruskal-Wallis Test

data:  grade by dose (vehicle, low, high)
chi-squared = 13.705, p-value = 0.00017

== Separate Mann-Whitney tests (each pair re-ranked), Holm ==
         vehicle        low
low  0.080024047         NA
high 0.004515358 0.01949527
== IL-6: classical ANOVA (raw) ==
            Df Sum Sq Mean Sq F value  Pr(>F)   
dose         2   7667    3834   9.031 0.00267 **
Residuals   15   6367     424                   
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
== IL-6: Welch ANOVA (raw) ==

	One-way analysis of means (not assuming equal variances)

data:  il6 and dose
F = 6.389, num df = 2.0000, denom df = 9.1343, p-value = 0.01838

== IL-6: Welch ANOVA (log) ==

	One-way analysis of means (not assuming equal variances)

data:  log(il6) and dose
F = 7.2782, num df = 2.0000, denom df = 9.1827, p-value = 0.01277

== IL-6: Kruskal-Wallis ==

	Kruskal-Wallis rank sum test

data:  il6 by dose
Kruskal-Wallis chi-squared = 11.178, df = 2, p-value = 0.003738

== IL-6: ratio high/vehicle, Welch on logs (unadjusted 95% CI) ==
ratio.mean in group high                    lower                    upper 
             3.560583382              1.601081480              7.918244121 
                       p 
             0.005980798