hello
I use lsmeans to adjust my data. the outcome shows the result with decimal df. I want to know is it normal that df will be decimal? and how can I infer df for lsmeans? and also is it normal that df is different from each other?
this is some part of my result
N | Condition.x | Genotype.x | lsmean | SE | df | lower.CL | upper.CL |
1 | C | B1 | 2.580171 | 0.150533 | 5.144451 | 2.196458 | 2.963884 |
2 | T | B1 | 1.39861 | 0.15061 | 5.16151 | 1.01507 | 1.782149 |
3 | C | DZ | 2.660867 | 0.150933 | 5.190571 | 2.277128 | 3.044606 |
4 | T | DZ | 1.489736 | 0.150499 | 5.126756 | 1.105725 | 1.873747 |
5 | C | LR41 | 2.52188 | 0.208292 | 18.82806 | 2.085651 | 2.958109 |
6 | T | LR41 | 1.383875 | 0.208298 | 18.84527 | 0.947661 | 1.820089 |
7 | C | LR410 | 2.684989 | 0.219836 | 23.41883 | 2.230673 | 3.139305 |
8 | T | LR410 | 1.313379 | 0.219908 | 23.45823 | 0.858956 | 1.767801 |
9 | C | LR100 | 2.802647 | 0.199137 | 15.78295 | 2.380023 | 3.225271 |
What SAS code did you submit?
leastsquare_root_lengh_R_1_2_3_4 <- lsmeans(rootlength_REP1_2_3_4,
pairwise ~ Condition.x* Genotype.x ,
adjust = "tukey",pbkrtest.limit = 6950,lmerTest.limit = 6950) ### Tukey-adjusted comparisons
R1234_LSMEANS_DATA <-
summary(leastsquare_root_lengh_R_1_2_3_4)
write.csv(R1234_LSMEANS_DATA,
"./LSmeans_R1234_Length.CSV")
this is the script that i use. I whant to know how df calculate for lsmeans and what is its meaning? thank you very much
This is not SAS code.
yes but just I what to know how df will be calculate ? and what mean dose it have?
I don't know what the language is that you used, and I don't know how that language does a calculation of non-integer degrees of freedom. You should really ask in a forum for that specific language, and the people there probably can explain what that language is doing.
this is R script. ok thank you
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