lsd: Analysis of Latin Square Design

In doebioresearch: Analysis of Design of Experiments for Biological Research

Description

The function gives ANOVA, R-square of the model, normality testing of residuals, SEm (standard error of mean), SEd (standard error of difference), interpretation of ANOVA results and multiple comparison test for means.

Usage

lsd(data, treatmentvector, row, column, MultipleComparisonTest)

Arguments

data	dependent variables
treatmentvector	vector containing treatments
row	vector for rows
column	vector for columns
MultipleComparisonTest	0 for no test, 1 for LSD test, 2 for Duncan test and 3 for HSD test

Value

ANOVA, interpretation of ANOVA, R-square, normality test result, SEm, SEd and multiple comparison test result

Examples

data(lsddata)
#LSD analysis with LSD test for Yield only
lsd(lsddata[4],lsddata$Treatment,lsddata$Row,lsddata$Column,1)
#LSD analysis with LSD test for Yield and Plant Height
lsd(lsddata[4:5],lsddata$Treatment,lsddata$Row,lsddata$Column,1)

Example output

$Yield
$Yield[[1]]
Analysis of Variance Table

Response: data2
          Df Sum Sq Mean Sq F value   Pr(>F)   
row        4  66.76  16.689  0.6374 0.645733   
column     4  42.33  10.582  0.4041 0.802178   
trt        4 957.97 239.491  9.1460 0.001253 **
Residuals 12 314.22  26.185                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

$Yield[[2]]
[1] "R Square 0.773"

$Yield[[3]]

	Shapiro-Wilk normality test

data:  model$residuals
W = 0.98241, p-value = 0.9283


$Yield[[4]]
[1] "Normality assumption is not violated"

$Yield[[5]]
[1] "SEm 2.2885 , SEd 3.2364"

$Yield[[6]]
[1] "The treatment means of one or more treatments are not same, so go for multiple comparison test"

$Yield[[7]]
$Yield[[7]][[1]]
  MSerror Df   Mean       CV  t.value      LSD
  26.1854 12 33.536 15.25873 2.178813 7.051468

$Yield[[7]][[2]]
  data2 groups
B 40.40      a
C 37.72      a
D 37.42      a
E 26.52      b
A 25.62      b



$Yield
$Yield[[1]]
Analysis of Variance Table

Response: data2
          Df Sum Sq Mean Sq F value   Pr(>F)   
row        4  66.76  16.689  0.6374 0.645733   
column     4  42.33  10.582  0.4041 0.802178   
trt        4 957.97 239.491  9.1460 0.001253 **
Residuals 12 314.22  26.185                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

$Yield[[2]]
[1] "R Square 0.773"

$Yield[[3]]

	Shapiro-Wilk normality test

data:  model$residuals
W = 0.98241, p-value = 0.9283


$Yield[[4]]
[1] "Normality assumption is not violated"

$Yield[[5]]
[1] "SEm 2.2885 , SEd 3.2364"

$Yield[[6]]
[1] "The treatment means of one or more treatments are not same, so go for multiple comparison test"

$Yield[[7]]
$Yield[[7]][[1]]
  MSerror Df   Mean       CV  t.value      LSD
  26.1854 12 33.536 15.25873 2.178813 7.051468

$Yield[[7]][[2]]
  data2 groups
B 40.40      a
C 37.72      a
D 37.42      a
E 26.52      b
A 25.62      b



$Plant_Height
$Plant_Height[[1]]
Analysis of Variance Table

Response: data2
          Df Sum Sq Mean Sq F value  Pr(>F)  
row        4 306.16  76.540  5.0666 0.01262 *
column     4  28.56   7.140  0.4726 0.75515  
trt        4  23.76   5.940  0.3932 0.80967  
Residuals 12 181.28  15.107                  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

$Plant_Height[[2]]
[1] "R Square 0.664"

$Plant_Height[[3]]

	Shapiro-Wilk normality test

data:  model$residuals
W = 0.96767, p-value = 0.5866


$Plant_Height[[4]]
[1] "Normality assumption is not violated"

$Plant_Height[[5]]
[1] "SEm 1.7382 , SEd 2.4582"

$Plant_Height[[6]]
[1] "All the treatment means are same so dont go for any multiple comparison test"

$Plant_Height[[7]]
$Plant_Height[[7]][[1]]
   MSerror Df  Mean       CV  t.value      LSD
  15.10667 12 18.36 21.16955 2.178813 5.355922

$Plant_Height[[7]][[2]]
  data2 groups
A  19.8      a
D  18.8      a
B  18.6      a
E  17.6      a
C  17.0      a

doebioresearch documentation built on July 8, 2020, 7:18 p.m.