myszy_002.R

ms6 <- lsmeans(model_mieszany,  
                    pairwise~ typ*traktowanie, 
                    adjust="tukey")

# $lsmeans
#  Group           lsmean         SE    df   lower.CL   upper.CL
#  condition 1 -0.2208147 0.02642544 14.22 -0.2774102 -0.1642192
#  condition 2 -0.3123998 0.02628429 14.06 -0.3687533 -0.2560464
#  condition 3 -0.3500326 0.02688922 14.71 -0.4074429 -0.2926222
#  condition 4 -0.3249601 0.02589164 13.06 -0.3808715 -0.2690487
# 
# Confidence level used: 0.95 
# 
# $contrasts
#  contrast                     estimate         SE     df t.ratio p.value
#  condition 1 - condition 2  0.09158510 0.02667834 151.64   3.433  0.0042
#  condition 1 - condition 3  0.12921784 0.03770058  14.47   3.427  0.0182
#  condition 1 - condition 4  0.10414537 0.03699569  13.63   2.815  0.0601
#  condition 2 - condition 3  0.03763274 0.03760179  14.39   1.001  0.7514
#  condition 2 - condition 4  0.01256026 0.03689500  13.55   0.340  0.9858
#  condition 3 - condition 4 -0.02507248 0.02668956 159.47  -0.939  0.7837
# 
# P value adjustment: tukey method for comparing a family of 4 estimates