Ejericios de ANOVA y kruskal wallis

Author

AY González García

Datos y librerias

library(MASS)
data("Cushings")
attach(Cushings)
library(gplots)

Warning: package 'gplots' was built under R version 4.2.3


Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

Ejercicios (pruebas ANOVA y post-hoc)

ejercicio 13.6

#prueba de diferencias
ANOVA2<-aov(Pregnanetriol~Type)
summary(ANOVA2)

            Df Sum Sq Mean Sq F value Pr(>F)  
Type         3  72.41   24.14   3.539 0.0305 *
Residuals   23 156.86    6.82                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#posthoc de variables pregnanetriol
TukeyHSD(ANOVA2)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = Pregnanetriol ~ Type)

$Type
     diff        lwr        upr     p adj
b-a -1.32 -5.0518826 2.41188263 0.7627013
c-a  3.06 -1.3160203 7.43602027 0.2416159
u-a -1.24 -5.4123716 2.93237162 0.8432729
c-b  4.38  0.4217407 8.33825927 0.0263648
u-b  0.08 -3.6518826 3.81188263 0.9999227
u-c -4.30 -8.6760203 0.07602027 0.0553182

#Garfico de posthoc
plot(TukeyHSD(ANOVA2))

#Graficos
plotmeans(Pregnanetriol~Type)

boxplot(Pregnanetriol~Type)

#Resultados: existen diferencias en el entre el grupo de pacientes con carcinoma y hiperplasia bilateral, según la pruba de posthoc.

Ejercicio 13.7

base de datos

library(readxl)
SLE_dataset1 <- read_excel("C:/Users/David/Downloads/SLE dataset1.xlsx")
View(SLE_dataset1)

desarollo de ejercicio

#prueba de diferencias
#ANOVA de variables AGE
ANOVA3<-aov(SLE_dataset1$Age~SLE_dataset1$Groups_NLSLEvsSLE)
summary(ANOVA3)

                                Df Sum Sq Mean Sq F value Pr(>F)  
SLE_dataset1$Groups_NLSLEvsSLE   1    526   526.1   4.279 0.0411 *
Residuals                      101  12419   123.0                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#posthoc de variable
TukeyHSD(ANOVA3)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = SLE_dataset1$Age ~ SLE_dataset1$Groups_NLSLEvsSLE)

$`SLE_dataset1$Groups_NLSLEvsSLE`
              diff       lwr      upr     p adj
Non-LN-LN 4.974429 0.2039998 9.744859 0.0411418

#Garfico de posthoc
plot(TukeyHSD(ANOVA3))

#ANOVA variable leptina

#prueba de diferencias
ANOVA4<-aov(SLE_dataset1$Leptin~SLE_dataset1$Groups_NLSLEvsSLE)
summary(ANOVA4)

                                Df Sum Sq Mean Sq F value Pr(>F)  
SLE_dataset1$Groups_NLSLEvsSLE   1   2453    2453   3.289 0.0727 .
Residuals                      101  75342     746                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#posthoc de variable
TukeyHSD(ANOVA4)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = SLE_dataset1$Leptin ~ SLE_dataset1$Groups_NLSLEvsSLE)

$`SLE_dataset1$Groups_NLSLEvsSLE`
               diff       lwr     upr     p adj
Non-LN-LN -10.74152 -22.49153 1.00849 0.0727291

#Garfico de posthoc
plot(TukeyHSD(ANOVA4))

#ANOVA variable leptina_BMI

#prueba de diferencias
ANOVA5<-aov(SLE_dataset1$Leptin_BMI~SLE_dataset1$Groups_NLSLEvsSLE)
summary(ANOVA5)

                                Df Sum Sq Mean Sq F value Pr(>F)  
SLE_dataset1$Groups_NLSLEvsSLE   1   3.06  3.0634   3.491 0.0646 .
Residuals                      101  88.63  0.8775                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#posthoc de variable
TukeyHSD(ANOVA5)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = SLE_dataset1$Leptin_BMI ~ SLE_dataset1$Groups_NLSLEvsSLE)

$`SLE_dataset1$Groups_NLSLEvsSLE`
                diff       lwr       upr     p adj
Non-LN-LN -0.3795779 -0.782583 0.0234272 0.0646027

#Garfico de posthoc
plot(TukeyHSD(ANOVA5))

#ANOVA variable adiponectina

#prueba de diferencias
ANOVA6<-aov(SLE_dataset1$Adiponectin~SLE_dataset1$Groups_NLSLEvsSLE)
summary(ANOVA6)

                                Df Sum Sq Mean Sq F value Pr(>F)  
SLE_dataset1$Groups_NLSLEvsSLE   1    506   505.5    6.81 0.0104 *
Residuals                      101   7497    74.2                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#posthoc de variable
TukeyHSD(ANOVA6)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = SLE_dataset1$Adiponectin ~ SLE_dataset1$Groups_NLSLEvsSLE)

$`SLE_dataset1$Groups_NLSLEvsSLE`
              diff       lwr       upr     p adj
Non-LN-LN -4.87602 -8.582551 -1.169488 0.0104409

#Garfico de posthoc
plot(TukeyHSD(ANOVA6))

#ANOVA variable adiponectina_BMI

#prueba de diferencias
ANOVA7<-aov(SLE_dataset1$Adiponectin_BMI~SLE_dataset1$Groups_NLSLEvsSLE)
summary(ANOVA7)

                                Df Sum Sq Mean Sq F value Pr(>F)  
SLE_dataset1$Groups_NLSLEvsSLE   1  0.858  0.8578   5.621 0.0196 *
Residuals                      101 15.412  0.1526                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#posthoc de variable
TukeyHSD(ANOVA7)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = SLE_dataset1$Adiponectin_BMI ~ SLE_dataset1$Groups_NLSLEvsSLE)

$`SLE_dataset1$Groups_NLSLEvsSLE`
                diff        lwr         upr     p adj
Non-LN-LN -0.2008565 -0.3689107 -0.03280225 0.0196405

#Garfico de posthoc
plot(TukeyHSD(ANOVA7))

#Funcion y graficos para cada variable
Grafico.ANOVA <- function(x, y){
  print(y)  
  par(mfrow = c(1,1))  
  boxplot(x, main = "",  ylab = "", xlab = "Grupos experimentales")
  plotmeans(x, ylab= "", xlab = "Grupos experimentales")
}
#Age vs grupo experimental
Grafico.ANOVA(SLE_dataset1$Age~SLE_dataset1$Groups_NLSLEvsSLE, SLE_dataset1$Age~SLE_dataset1$Groups_NLSLEvsSLE)

SLE_dataset1$Age ~ SLE_dataset1$Groups_NLSLEvsSLE

#leptina vs grupo experimental
Grafico.ANOVA(SLE_dataset1$Leptin~SLE_dataset1$Groups_NLSLEvsSLE, SLE_dataset1$Leptin~SLE_dataset1$Groups_NLSLEvsSLE)

SLE_dataset1$Leptin ~ SLE_dataset1$Groups_NLSLEvsSLE

#leptina_BMI vs grupo experimental
Grafico.ANOVA(SLE_dataset1$Leptin_BMI~SLE_dataset1$Groups_NLSLEvsSLE, SLE_dataset1$Leptin_BMI~SLE_dataset1$Groups_NLSLEvsSLE)

SLE_dataset1$Leptin_BMI ~ SLE_dataset1$Groups_NLSLEvsSLE

#adiponectina vs grupo experimental
Grafico.ANOVA(SLE_dataset1$Adiponectin~SLE_dataset1$Groups_NLSLEvsSLE, SLE_dataset1$Adiponectin~SLE_dataset1$Groups_NLSLEvsSLE)

SLE_dataset1$Adiponectin ~ SLE_dataset1$Groups_NLSLEvsSLE

#adiponectina_BMI vs grupo experimental
Grafico.ANOVA(SLE_dataset1$Adiponectin_BMI~SLE_dataset1$Groups_NLSLEvsSLE, SLE_dataset1$Adiponectin_BMI~SLE_dataset1$Groups_NLSLEvsSLE)

SLE_dataset1$Adiponectin_BMI ~ SLE_dataset1$Groups_NLSLEvsSLE