Version: 0.2
Date: 2019-08-13
Title: Incomplete Split-Plot Designs
Author: Baidya Nath Mandal [aut, cre], Sukanta Dash [aut], Rajender Parsad [aut]
Maintainer: Baidya Nath Mandal <mandal.stat@gmail.com>
Depends: R (≥ 3.5.0)
Imports: ibd
Description: A collection of several functions related to construction and analysis of incomplete split-plot designs. The package contains functions to obtain and analyze incomplete split-plot designs for three kinds of situations namely (i) when blocks are complete with respect to main plot treatments and main plots are incomplete with respect to subplot treatments, (ii) when blocks are incomplete with respect to main plot treatments and main plots are complete with respect to subplot treatments and (iii) when blocks are incomplete with respect to main plot treatments and main plots are incomplete with respect to subplot treatments.
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Packaged: 2019-08-13 10:56:08 UTC; b
Repository: CRAN
Date/Publication: 2019-08-19 10:20:03 UTC

Analysis of variance of data from an incomplete split-plot design

Description

This function performs analysis of variance of data from experiments using an incomplete split-plot design for three types of situations namely (i) blocks are complete with respect to main plot treatments and mainplots are incomplete with respect to subplot treatments, (ii) blocks are incomplete with respect to main plot treatments and mainplots are complete with respect to subplot treatments and (iii) blocks are incomplete with respect to main plot treatments and mainplots are also incomplete with respect to subplot treatments.

Usage

aov.ispd(obs, block, mp, sp, y, incomplete.block = FALSE, incomplete.mp = TRUE)

Arguments

obs

observation numbers

block

block

mp

main plot treatment

sp

subplot treatment

y

response variable

incomplete.block

Are blocks incomplete? Default is FALSE

incomplete.mp

Are main plots incomplete? Default is TRUE

Value

Returns ANOVA table of incomplete split-plot design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Examples

data(cmis)
with(cmis, aov.ispd(obs, block, mp, sp, y, incomplete.block = FALSE, incomplete.mp = TRUE))
data(imcs)
with(imcs, aov.ispd(obs, block, mp, sp, y, incomplete.block = TRUE, incomplete.mp = FALSE))
data(imis)
with(imis, aov.ispd(obs, block, mp, sp, y, incomplete.block = TRUE, incomplete.mp = TRUE))

Analysis of variance of data from an incomplete split-plot design with complete blocks and incomplete main plots

Description

This function performs analysis of variance of data from experiments using an incomplete split-plot design for the situation when blocks are complete with respect to main plot treatments and mainplots are incomplete with respect to subplot treatments

Usage

aov.ispd.cmis(obs, block, mp, sp, y)

Arguments

obs

observation numbers

block

block

mp

main plot treatment

sp

subplot treatment

y

response variable

Value

Returns ANOVA table of incomplete split-plot design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Analysis of variance of data from an incomplete split-plot design with incomplete blocks and complete main plots

Description

This function performs analysis of variance of data from experiments using an incomplete split-plot design for the situation when blocks are incomplete with respect to main plot treatments and mainplots are complete with respect to subplot treatments

Usage

aov.ispd.imcs(obs, block, mp, sp, y)

Arguments

obs

observation numbers

block

block

mp

main plot treatment

sp

subplot treatment

y

response variable

Value

Returns ANOVA table of incomplete split-plot design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Analysis of variance of data from an incomplete split-plot design with incomplete blocks and incomplete main plots

Description

This function performs analysis of variance of data from experiments using an incomplete split-plot design for the situation when blocks are incomplete with respect to main plot treatments and mainplots are incomplete with respect to subplot treatments

Usage

aov.ispd.imis(obs, block, mp, sp, y)

Arguments

obs

observation numbers

block

block

mp

main plot treatment

sp

subplot treatment

y

response variable

Value

Returns ANOVA table of incomplete split-plot design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Data from an experiment using incomplete split-plot design

Description

Data from an experiment using incomplete split-plot design where blocks are complete with respect to main plot treatments and main plots are incomplete with respect to subplot treatments

Usage

data("cmis")

Format

A data frame with 36 observations on the following 5 variables.

obs

Observations

block

Blocks

mp

Main plot treatments

sp

Subplot treatments

y

The response variable

Examples

data(cmis)

Data from an experiment using incomplete split-plot design

Description

Data from an experiment using incomplete split-plot design where blocks are incomplete with respect to main plot treatments and main plots are complete with respect to subplot treatments

Usage

data("imcs")

Format

A data frame with 18 observations on the following 5 variables.

obs

Observations

block

Blocks

mp

Main plot treatments

sp

Subplot treatments

y

The response variable

Examples

data(imcs)

Data from an experiment using incomplete split-plot design

Description

Data from an experiment using incomplete split-plot design where blocks are incomplete with respect to main plot treatments and main plots are also incomplete with respect to subplot treatments

Usage

data("imis")

Format

A data frame with 36 observations on the following 5 variables.

obs

Observations

block

Blocks

mp

Main plot treatments

sp

Subplot treatments

y

The response variable

Examples

data(imis)

Incomplete split-plot design for given number of blocks, number of main plot treatments, number of subplot treatments, number of main plot treatments in blocks and / or number of subplot treatments in main plots

Description

This function generates an incomplete split-plot design with given number of main plot treatments(v1), number of subplot treatments (v2), number of blocks(b) and block size(k). The incomplete split-plot design may be one of the three kinds: (i) blocks are complete with respect to main plot treatments and mainplots are incomplete with respect to subplot treatments, (ii) blocks are incomplete with respect to main plot treatments and mainplots are complete with respect to subplot treatments and (iii) blocks are incomplete with respect to main plot treatments and mainplots are also incomplete with respect to subplot treatments.

Usage

ispd(v1,v2,b,k1 = NULL,k2 = NULL)

Arguments

v1

number of main plot treatments

v2

number of subplot treatments

b

number of blocks

k1

number of main plot treatments in each block. If k1 is not specified, it is assumed that k1 = v1

k2

number of subplot treatments in each main plot. If k2 is not specified, it is assumed that k2 = v2

Value

A list containing parameters, design layout and column layout of design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Examples

ispd(v1 = 3, v2 = 4, b = 3, k1 = 2)
ispd(v1 = 3, v2 = 3, b = 3, k2 = 2)
ispd(v1 = 4, b = 6, k1 = 2, v2 = 3, k2 = 2)

Incomplete split-plot design for given number of main plot treatments, number of subplot treatments, number of blocks and number of subplot treatments in each main plot

Description

This function generate an incomplete split-plot design for given number of main plot treatments, number of subplot treatments, number of blocks and number of subplot treatments in each main plot

Usage

ispd.cmis(v1,v2,b,k2)

Arguments

v1

number of main plot treatments

v2

number of subplot treatments

b

number of block

k2

number of subplot treatments in each main plot

Value

A list containing parameters, design layout and column layout of design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Incomplete split-plot design for given number of main plot treatments, number of subplot treatments, number of blocks and number of main plot treatments in each block

Description

This function generate an incomplete split-plot design for given number of main plot treatments, number of subplot treatments, number of blocks and number of main plot treatments in each block

Usage

ispd.imcs(v1,b,k1,v2)

Arguments

v1

number of main plot treatments

b

number of blocks

k1

number of main plot treatments in each block

v2

number of subplot treatments

Value

A list containing parameters, design layout and column layout of design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Incomplete split-plot design for given number of main plot treatments, number of subplot treatments, number of blocks, number of main plot treatments in each block and number of subplot treatments in each main plot

Description

This function generate an incomplete split-plot design for given number of main plot treatments, number of subplot treatments, number of blocks, number of main plot treatments in each block and number of subplot treatments in each main plot

Usage

ispd.imis(v1,b,k1,v2,k2)

Arguments

v1

number of main plot treatments

b

number of blocks

k1

number of main plot treatments in each block

v2

number of subplot treatments

k2

number of subplot treatments in each main plot

Value

A list containing parameters, design layout and column layout of design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>

Complete split-plot design for given number of main plot treatments, number of subplot treatments and number of blocks

Description

This function generate a complete split-plot design for given number of main plot treatments, number of subplot treatments and number of blocks

Usage

spd(v1,v2,b)

Arguments

v1

number of main plot treatments

v2

number of subplot treatments

b

number of block

Value

A list containing parameters, design layout and column layout of design

Author(s)

Baidya Nath Mandal <mandal.stat@gmail.com>