Hello everyone, I have questions about the model setting for the split-split plot design. My data set includes 4 treatment combinations (main-plot), 3 cultivars (sub-plot), and we collect the data at 3 growth stages (sub-sub plot). Each treatment has 2 or 3 replicates. The treatment combinations were: I want to run an ANOVA test to see the effect of treatments on the collected data (Obs). and here is my questions: 1) What is the proper way to code the treatment? one way is to separate inoculation (Treat_I) and fungicide treatment (Treat_F) and code as two factors the problem is, the fungicide treatment only applied at stage 3, I try to code this treatment as NA at Stage 1 and 2, will this cause problems during analysis? another way is to code them as one factor that has 4 combinations (Treat), but it may not be the correct way too. 2) Should I nested the treatment within Stage? Here is some sample data and my model: Data sample;
Plot_ID$ Cultivars$ Rep$ Treat$ Treat_I$ Treat_F$ Treat_F_2$ Stage$ Obs
cards;
18QM1011 LD13 1 Inoc/no Inoc . no V4_R1 24.24
18QM1033 Williams 1 NIC/yes NIC . yes V4_R1 120.6
18QM2022 LD12 2 Inoc/no Inoc . no V4_R1 54.74
18QM3011 LD12 3 Inoc/yes Inoc . yes V4_R1 88.46
18QM3033 LD12 3 Inoc/no Inoc . no V4_R1 43.5
18QM1012 Williams 1 Inoc/no Inoc . no V4_R1 79.82
18QM1041 LD13 1 NIC/no NIC . no V4_R1 42.52
18QM2023 Williams 2 Inoc/no Inoc . no V4_R1 242.96
18QM3012 LD13 3 Inoc/yes Inoc . yes V4_R1 70.4
18QM3041 Williams 3 NIC/no NIC . no V4_R1 95.26
18QM1013 LD12 1 Inoc/no Inoc . no V4_R1 37.4
18QM1042 Williams 1 NIC/no NIC . no V4_R1 133.5
18QM2031 LD13 2 NIC/no NIC . no V4_R1 45.04
18QM3013 Williams 3 Inoc/yes Inoc . yes V4_R1 135
18QM3042 LD13 3 NIC/no NIC . no V4_R1 43.82
18QM1021 LD12 1 Inoc/yes Inoc . yes V4_R1 332.98
18QM1043 LD12 1 NIC/no NIC . no V4_R1 63.9
18QM2032 LD12 2 NIC/no NIC . no V4_R1 16.9
18QM3021 Williams 3 NIC/yes NIC . yes V4_R1 93.84
18QM3043 LD12 3 NIC/no NIC . no V4_R1 41.34
18QM1022 LD13 1 Inoc/yes Inoc . yes V4_R1 40.66
18QM2011 LD13 2 Inoc/yes Inoc . yes V4_R1 78.38
18QM2033 Williams 2 NIC/no NIC . no V4_R1 66.14
18QM3022 LD13 3 NIC/yes NIC . yes V4_R1 97.86
18QM1023 Williams 1 Inoc/yes Inoc . yes V4_R1 254.92
18QM2012 LD12 2 Inoc/yes Inoc . yes V4_R1 37.42
18QM2041 LD13 2 NIC/yes NIC . yes V4_R1 42.92
18QM3023 LD12 3 NIC/yes NIC . yes V4_R1 104.9
18QM1031 LD13 1 NIC/yes NIC . yes V4_R1 97.34
18QM2013 Williams 2 Inoc/yes Inoc . yes V4_R1 202.26
18QM2042 Williams 2 NIC/yes NIC . yes V4_R1 122.58
18QM3031 Williams 3 Inoc/no Inoc . no V4_R1 187.28
18QM1032 LD12 1 NIC/yes NIC . yes V4_R1 55.52
18QM2021 LD13 2 Inoc/no Inoc . no V4_R1 56.42
18QM2043 LD12 2 NIC/yes NIC . yes V4_R1 62.4
18QM3032 LD13 3 Inoc/no Inoc . no V4_R1 114.36
18QM1022 LD13 1 Inoc/yes Inoc . yes R2_R3 106.68
18QM2011 LD13 2 Inoc/yes Inoc . yes R2_R3 313.62
18QM2033 Williams 2 NIC/no NIC . no R2_R3 166.98
18QM3022 LD13 3 NIC/yes NIC . yes R2_R3 392.5
18QM1023 Williams 1 Inoc/yes Inoc . yes R2_R3 56.72
18QM2012 LD12 2 Inoc/yes Inoc . yes R2_R3 123.76
18QM3023 LD12 3 NIC/yes NIC . yes R2_R3 184.68
18QM1031 LD13 1 NIC/yes NIC . yes R2_R3 265.96
18QM2013 Williams 2 Inoc/yes Inoc . yes R2_R3 480.54
18QM2042 Williams 2 NIC/yes NIC . yes R2_R3 741.88
18QM3031 Williams 3 Inoc/no Inoc . no R2_R3 79.52
18QM1032 LD12 1 NIC/yes NIC . yes R2_R3 86.04
18QM2021 LD13 2 Inoc/no Inoc . no R2_R3 236.32
18QM2043 LD12 2 NIC/yes NIC . yes R2_R3 90.46
18QM3032 LD13 3 Inoc/no Inoc . no R2_R3 251.68
18QM1033 Williams 1 NIC/yes NIC . yes R2_R3 35.24
18QM2022 LD12 2 Inoc/no Inoc . no R2_R3 174.82
18QM3011 LD12 3 Inoc/yes Inoc . yes R2_R3 324.54
18QM3033 LD12 3 Inoc/no Inoc . no R2_R3 136.52
18QM1012 Williams 1 Inoc/no Inoc . no R2_R3 27.36
18QM1041 LD13 1 NIC/no NIC . no R2_R3 86.8
18QM2023 Williams 2 Inoc/no Inoc . no R2_R3 201.6
18QM3012 LD13 3 Inoc/yes Inoc . yes R2_R3 267.86
18QM3041 Williams 3 NIC/no NIC . no R2_R3 305.4
18QM1013 LD12 1 Inoc/no Inoc . no R2_R3 29.46
18QM1042 Williams 1 NIC/no NIC . no R2_R3 89.2
18QM2031 LD13 2 NIC/no NIC . no R2_R3 71.1
18QM3013 Williams 3 Inoc/yes Inoc . yes R2_R3 426.38
18QM3042 LD13 3 NIC/no NIC . no R2_R3 193.2
18QM1021 LD12 1 Inoc/yes Inoc . yes R2_R3 51.4
18QM1043 LD12 1 NIC/no NIC . no R2_R3 78.86
18QM2032 LD12 2 NIC/no NIC . no R2_R3 160.92
18QM3021 Williams 3 NIC/yes NIC . yes R2_R3 269.04
18QM3043 LD12 3 NIC/no NIC . no R2_R3 225.86
18QM1012 Williams 1 Inoc/no Inoc no no R5 523.32
18QM1042 Williams 1 NIC/no NIC no no R5 327.4
18QM3021 Williams 3 NIC/yes NIC yes yes R5 252.5
18QM1013 LD12 1 Inoc/no Inoc no no R5 157.36
18QM1043 LD12 1 NIC/no NIC no no R5 281.04
18QM3022 LD13 3 NIC/yes NIC yes yes R5 75.54
18QM1021 LD12 1 Inoc/yes Inoc yes yes R5 212.98
18QM2013 Williams 2 Inoc/yes Inoc yes yes R5 289.54
18QM3023 LD12 3 NIC/yes NIC yes yes R5 178.8
18QM1022 LD13 1 Inoc/yes Inoc yes yes R5 245.74
18QM2021 LD13 2 Inoc/no Inoc no no R5 314.52
18QM3031 Williams 3 Inoc/no Inoc no no R5 67.96
18QM1031 LD13 1 NIC/yes NIC yes yes R5 65
18QM2031 LD13 2 NIC/no NIC no no R5 287.78
18QM3032 LD13 3 Inoc/no Inoc no no R5 266.26
18QM1032 LD12 1 NIC/yes NIC yes yes R5 581.22
18QM3011 LD12 3 Inoc/yes Inoc yes yes R5 180.02
18QM3033 LD12 3 Inoc/no Inoc no no R5 265.14
18QM1033 Williams 1 NIC/yes NIC yes yes R5 332.46
18QM3012 LD13 3 Inoc/yes Inoc yes yes R5 93.02
18QM3041 Williams 3 NIC/no NIC no no R5 242
18QM1041 LD13 1 NIC/no NIC no no R5 278.92
18QM3013 Williams 3 Inoc/yes Inoc yes yes R5 139.82
18QM3043 LD12 3 NIC/no NIC no no R5 60.46
;;;
proc mixed data=sample method=REML;
class Plot_ID Seed Rep Treat Treat_I Treat_F Stage;
model Obs = Rep Seed
Treat_I Treat_I*Seed
Treat_F Treat_F*Seed
Stage Stage*Treat_I Stage*Treat_F Stage*Treat_I*Treat_F;
random Rep Rep*Seed Rep*Treat_I Rep*Treat_F Rep*Treat_I*Treat_F;
run;quit; Could anyone give me some suggestions? Thanks!!
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