Dear all,
I am new user for R program and I am
looking for somebody to help me with Manova and discriminant function analysis
DFA .
I have four measurement traits for bird
species (weight, wing length, tarsus length and bill length) and I would like
to test for differences in body size between males and females of this species.
FIRST, I applied MANOVA using (weight,
wing length, tarsus length and bill length) as dependent variables and sex as
an independent variable. In order to identify the significance of sex
differences for each dependent variable using this form:
rm
data1<-read.csv("C:/Users/Desktop/CP/CP_NOMISS.csv")
names (data1)
attached(data1)
head(data1)
manova1 <- manova (cbind (Weight,
Wing.Length, Tarsus.Length, Bill.Length)~ as.factor (Sex), data=data1)
summary (manova1)
summary.aov(manova1)
After that I got four tables (one table
for each variable)
My questions are:
1. Is what I did correct and enough to
get Manova results?
2. what is the most important result can
describe the difference is it F value or Pr(>F) value
2. How I can describe the results in
figure?
SECOND, I applied discriminant function
analysis (DFA) on the four morphological characters using the package MASS in
order to identify the variable that differed most between males and females
using
this form:
rm
library (MASS)
data1<-read.csv("C:/Users/Desktop/CP/CP_NOMISS.csv")
head(data1)
attach (data1)
data1
plot(data1[ ,c(2,3,4,5)], col=data1[ ,1])
data1.lda <- lda(SEX~WG + WL + TL +
BL, data=data1)
data1.lda
After that I got this result:
Coefficients of linear discriminants:
LD1
WG -0.001040297
WL -0.011554912
TL
0.030233583
BL
0.498226667
1.Is what I did enough to say the
variable that differed most between males and females is BL 0.498. And does
this difference is reliable?
OR there are other steps I have to do.
Please excuse the long email.
Thank you very much in advance for any
help you can provide.
Best regards,Mohammed
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