I've done a standard two way ANOVA using glm on the dependent variable "clutchsize" with the two factors "treatment" (which has 3 levels called 1, 2, and 3) and "species" (which has two levels called 1 and 2). Apparently there is no significant interaction term. Then I did Tukey's HSD and found that there were significant differences between species at only one of the three treatment levels, treatment level 1. Are these in fact conflicting results? ##ANOVA RESULTS
summary(aov((clutchsize~treatment*species)))
Df Sum Sq Mean Sq F value Pr(>F) treatment 1 29.26 29.264 7.0230 0.00884 ** species 1 138.14 138.143 33.1526 4.13e-08 *** treatment:species 1 8.11 8.110 1.9464 0.16487 Residuals 163 679.20 4.167 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ##TUKEY HSD RESULTS
TukeyHSD(aov(clutchsize~treatment*species))
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = clutchsize ~ treatment * species)
$treatment
diff lwr upr p adj
2-1 1.3245614 0.4184292 2.2306936 0.0020030
3-1 1.0416667 0.1316071 1.9517262 0.0204117
3-2 -0.2828947 -1.1806793 0.6148899 0.7368331
$species
diff lwr upr p adj
2-1 -1.89988 -2.544747 -1.255013 0
$`treatment:species`
diff lwr upr p adj
2:1-1:1 1.1791506 -0.19269072 2.5509919 0.1364846
3:1-1:1 0.6476190 -0.73345324 2.0286913 0.7550479
1:2-1:1 -2.4225564 -4.08045729 -0.7646555 0.0005858
2:2-1:1 -0.8357143 -2.46652980 0.7951012 0.6787094
3:2-1:1 -0.6357143 -2.26652980 0.9951012 0.8706501
3:1-2:1 -0.5315315 -1.89354633 0.8304833 0.8701101
1:2-2:1 -3.6017070 -5.24376636 -1.9596476 0.0000000
2:2-2:1 -2.0148649 -3.62957317 -0.4001566 0.0055886
3:2-2:1 -1.8148649 -3.42957317 -0.2001566 0.0177862
1:2-3:1 -3.0701754 -4.71995456 -1.4203963 0.0000041
2:2-3:1 -1.4833333 -3.10589150 0.1392248 0.0944158
3:2-3:1 -1.2833333 -2.90589150 0.3392248 0.2077935
2:2-1:2 1.5868421 -0.27701672 3.4507009 0.1438444
3:2-1:2 1.7868421 -0.07701672 3.6507009 0.0684872
3:2-2:2 0.2000000 -1.63980803 2.0398080 0.9995894