gomez.fractionalfactorial {agridat} | R Documentation

## Rice fractional factorial experiment 1/2 2^6.

### Description

Rice fractional factorial experiment 1/2 2^6. Two reps with 2 blocks in each rep.

### Format

A data frame with 64 observations on the following 6 variables.

`yield`

  grain yield in tons/ha

`rep`

  replicate, 2 levels

`block`

  block within rep, 2 levels

`trt`

  treatment, levels (1) to abcdef

`col`

  column position in the field

`row`

  row position in the field

### Details

Grain yield from a 2^6 fractional factorial experiment in blocks of 16 plots each, with two replications.

Gomez has some inconsistencies. One example:

Page 171: treatment (1) in rep 1, block 2 and rep 2, block 1.

Page 172: treatment (1) in Rep 1, block 1 and rep 2, block 1.

This data uses the layout shown on page 171.

### Source

Gomez, K.A. and Gomez, A.A.. 1984, Statistical Procedures for Agricultural Research. Wiley-Interscience. Page 171-172.

Used with permission of Kwanchai Gomez.

### Examples

    data(gomez.fractionalfactorial)
    dat <- gomez.fractionalfactorial

    # trt abcdef has the highest yield
    # Gomez, Figure 4.8
    if(require(desplot)){
      desplot(yield~col*row, dat,
              # aspect unknown
              text=trt, shorten="none", show.key=FALSE, cex=1,
              main="gomez.fractionalfactorial - treatment & yield")
    }

    # Split treatment into individual factors
    dat <- transform(dat,
                     a = -1 + 2 * grepl('a',trt),
                      b = -1 + 2 * grepl('b',trt),
                     c = -1 + 2 * grepl('c',trt),
                     d = -1 + 2 * grepl('d',trt),
                     e = -1 + 2 * grepl('e',trt),
                     f = -1 + 2 * grepl('f',trt))

    # Gomez table 4.24, trt SS totalled together.
    # Why didn't Gomez nest block within rep?
    m0 <- lm(yield ~ rep * block + trt, dat)
    anova(m0)

    # Gomez table 4.24, trt SS split apart
    m1 <- lm(yield ~ rep * block + (a+b+c+d+e+f)^3, dat)
    anova(m1)

    ## Not run:
      require(FrF2)
      aliases(m1)
      MEPlot(m1, select=3:8,
             main="gomez.fractionalfactorial - main effects plot")

    ## End(Not run)

[Package agridat version 1.16 Index]