With two variables there are no combinations with less than 2 observations.
Here's the part of the data you provided:
> df <- structure(list(V1 = c(200, 200, 200, 200, 200, 200, 200, 200,
200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 500, 500, 500,
500, 500, 500, 500, 350, 350, 350, 350, 350, 200, 200, 200, 200,
200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 500, 500,
500, 500, 500, 350, 350, 350, 350, 350, 350, 350, 350, 350, 350,
350, 350, 350, 350, 350, 350, 350, 350, 350, 350, 500, 500, 500,
500, 500, 500, 500, 500, 500, 500, 350, 350, 350, 350, 350, 500,
500, 500, 500, 500), V2 = c(16, 16, 16, 16, 16, 8, 8, 8, 8, 8,
8, 8, 8, 8, 8, 16, 16, 16, 16, 16, 8, 8, 8, 8, 8, 8, 8, 8, 8,
8, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 16, 16, 16, 16, 16,
8, 8, 8, 8, 8, 16, 16, 16, 16, 16, 8, 8, 8, 8, 8, 16, 16, 16,
16, 16, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 16, 16, 16, 16,
16, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24), V3 = c(16, 16, 16,
16, 16, 16, 16, 16, 16, 16, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 23,
23, 23, 23, 23, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 23, 23, 23, 23,
23, 23, 23, 23, 23, 23, 16, 16, 16, 16, 16, 9, 9, 9, 9, 9, 23,
23, 23, 23, 23, 16, 16, 16, 16, 16, 23, 23, 23, 23, 23, 16, 16,
16, 16, 16, 23, 23, 23, 23, 23, 16, 16, 16, 16, 16, 9, 9, 9,
9, 9)), class = "data.frame", row.names = c(NA, -90L))
> xtabs(~V1+V2+V3, df) # There are 9 cells with 0 entries. That is the problem.
, , V3 = 9
V2
V1 8 16 24
200 5 0 5
350 5 5 0
500 0 5 5
, , V3 = 16
V2
V1 8 16 24
200 5 5 0
350 0 5 5
500 5 0 5
, , V3 = 23
V2
V1 8 16 24
200 0 5 5
350 5 0 5
500 5 5 0
> xtabs(~V1+V2, df) # No cells < 2 with V1, V2
V2
V1 8 16 24
200 10 10 10
350 10 10 10
500 10 10 10
> xtabs(~V1+V3, df) # No cells < 2 with V1, V3
V3
V1 9 16 23
200 10 10 10
350 10 10 10
500 10 10 10
> xtabs(~V2+V3, df) # No cells < 2 with V2, V3
V3
V2 9 16 23
8 10 10 10
16 10 10 10
24 10 10 10
David L. Carlson
Department of Anthropology
Texas A&M University
-----Original Message-----
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Yectli Huerta
via R-help
Sent: Monday, November 12, 2018 6:25 PM
To: r-help@r-project.org
Subject: Re: [R] semiparametric manova
thanks for the replies.
i don't believe the data is the problem. here you see how i used 3 variables
and it fails,
but when i use any combination of 2 variables, it does work
> head(df)
V1 V2 V3 V4 V5 V6 V7
1 200 16 16 3 64 5.584092e+13 1.616745e+12
2 200 16 16 3 64 5.589262e+13 1.715906e+12
3 200 16 16 3 64 5.588578e+13 1.714084e+12
4 200 16 16 3 64 5.588061e+13 1.651920e+12
5 200 16 16 3 64 5.589810e+13 1.624824e+12
6 200 8 16 1 48 5.585124e+13 1.689478e+12
> library(MANOVA.RM)
> df$V1
[1] 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 500 500 500 500
[20] 500 500 500 500 500 500 350 350 350 350 350 200 200 200 200 200 200 200 200
[39] 200 200 200 200 200 200 200 500 500 500 500 500 350 350 350 350 350 350 350
[58] 350 350 350 350 350 350 350 350 350 350 350 350 350 500 500 500 500 500 500
[77] 500 500 500 500 350 350 350 350 350 500 500 500 500 500
> df$V2
[1] 16 16 16 16 16 8 8 8 8 8 8 8 8 8 8 16 16 16 16 16 8 8 8 8 8
[26] 8 8 8 8 8 24 24 24 24 24 24 24 24 24 24 16 16 16 16 16 8 8 8 8 8
[51] 16 16 16 16 16 8 8 8 8 8 16 16 16 16 16 24 24 24 24 24 24 24 24 24 24
[76] 16 16 16 16 16 24 24 24 24 24 24 24 24 24 24
> df$V3
[1] 16 16 16 16 16 16 16 16 16 16 9 9 9 9 9 9 9 9 9 9 23 23 23 23 23
[26] 9 9 9 9 9 9 9 9 9 9 23 23 23 23 23 23 23 23 23 23 16 16 16 16 16
[51] 9 9 9 9 9 23 23 23 23 23 16 16 16 16 16 23 23 23 23 23 16 16 16 16 16
[76] 23 23 23 23 23 16 16 16 16 16 9 9 9 9 9
>
> MANOVA.wide(cbind(V6,V7)~V1*V2*V3,data=df,seed=1234)
Error in MANOVA.wide(cbind(V6, V7) ~ V1 * V2 * V3, data = df, seed = 1234) :
There is at least one factor-level combination
with less than 2 observations!
> MANOVA.wide(cbind(V6,V7)~V1*V2,data=df,seed=1234)
Call:
cbind(V6, V7) ~ V1 * V2
Wald-Type Statistic (WTS):
Test statistic df p-value
V1 17.870 4 0.001
V2 20.392 4 0.000
V1:V2 24.127 8 0.002
....
> MANOVA.wide(cbind(V6,V7)~V1*V3,data=df,seed=1234)
Call:
cbind(V6, V7) ~ V1 * V3
Wald-Type Statistic (WTS):
Test statistic df p-value
V1 18.566 4 0.001
V3 19.894 4 0.001
V1:V3 27.330 8 0.001
...
> MANOVA.wide(cbind(V6,V7)~V2*V3,data=df,seed=1234)
Call:
cbind(V6, V7) ~ V2 * V3
Wald-Type Statistic (WTS):
Test statistic df p-value
V2 20.139 4 0.000
V3 19.947 4 0.001
V2:V3 32.088 8 0.000
....
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