Package install

Data import

Data structure

str(d1)
## 'data.frame':    54 obs. of  4 variables:
##  $ subject   : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ sex       : Factor w/ 2 levels "female","male": 2 2 2 2 2 2 2 2 2 2 ...
##  $ group     : Factor w/ 2 levels "con","sevo2": 1 1 1 1 1 1 1 1 1 1 ...
##  $ mEPSC_ampl: num  17.1 19.2 26.5 21.4 22.3 ...

Explorative data analysis with graphics

Variance component analysis using plot

Two Way ANOVA analysis

Modleing with interaction

md1=aov(d1[,4]~group*sex, data=d1)
summary(md1)
##             Df Sum Sq Mean Sq F value   Pr(>F)    
## group        1   48.7    48.7   1.671 0.202118    
## sex          1  498.1   498.1  17.084 0.000136 ***
## group:sex    1    1.9     1.9   0.065 0.799187    
## Residuals   50 1457.7    29.2                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Result of interaction

interction()
## Accoring to the results,the p value of interaction is 0.799 
##  ,there is no statistically significant interaction between group and sex.

Model diagnostics

par(mfrow=c(2,2))
plot(md1)

Normality test

SWT
## 
##  Shapiro-Wilk normality test
## 
## data:  residuals(md1)
## W = 0.97189, p-value = 0.2331
SWT_result()
## Accoring to the results, the p value of Shapiro-Wilk test is 
##  p = 0.233 
##  which is greater than 0.05, so normality assumption can be accepted

Equal variance test

LT
LT_result()
## The p-value of Levene test is 
##  p = 0.291 
##  which is greater than 0.05, so equal variances can be assumed.

Post hoc test with nested model

We use nested model for post hoc test(to compare group within each sex). There are only one test, so we do not use p-value adjustment.

p
##                       Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)          19.413230   1.443047 13.452947 3.060434e-18
## sexmale               5.711841   2.040776  2.798857 7.266738e-03
## sexfemale:groupsevo2  1.524599   2.079651  0.733103 4.669189e-01
## sexmale:groupsevo2    2.276802   2.079651  1.094800 2.788502e-01
nm_result1()
## 1.The result of nested model in female 
##  p = 0.467 
##  statistically significant difference exist between groups
nm_result2()
## 2.The result of nested model in male 
##  p = 0.279 
##  statistically significant difference exist between groups