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Factor_Analysis.md

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Factor Analysis

Murat Koptur 24 Ağustos 2018

library(readr)
library(knitr)
library(psych)
bfi <- read_csv("../data/bfi.csv", 
    col_types = cols(X1 = col_skip(), age = col_skip(), 
        education = col_skip(), gender = col_skip()))
## Warning: Missing column names filled in: 'X1' [1]

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

## Warning in read_tokens_(data, tokenizer, col_specs, col_names, locale_, :
## length of NULL cannot be changed

kable(head(bfi))
A1 A2 A3 A4 A5 C1 C2 C3 C4 C5 E1 E2 E3 E4 E5 N1 N2 N3 N4 N5 O1 O2 O3 O4 O5
2 4 3 4 4 2 3 3 4 4 3 3 3 4 4 3 4 2 2 3 3 6 3 4 3
2 4 5 2 5 5 4 4 3 4 1 1 6 4 3 3 3 3 5 5 4 2 4 3 3
5 4 5 4 4 4 5 4 2 5 2 4 4 4 5 4 5 4 2 3 4 2 5 5 2
4 4 6 5 5 4 4 3 5 5 5 3 4 4 4 2 5 2 4 1 3 3 4 3 5
2 3 3 4 5 4 4 5 3 2 2 2 5 4 5 2 3 4 4 3 3 3 4 3 3
6 6 5 6 5 6 6 6 1 3 2 1 6 5 6 3 5 2 2 3 4 3 5 6 1 
KMO(bfi)
## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = bfi)
## Overall MSA =  0.85
## MSA for each item = 
##   A1   A2   A3   A4   A5   C1   C2   C3   C4   C5   E1   E2   E3   E4   E5 
## 0.74 0.84 0.87 0.87 0.90 0.83 0.79 0.85 0.82 0.86 0.83 0.88 0.89 0.87 0.89 
##   N1   N2   N3   N4   N5   O1   O2   O3   O4   O5 
## 0.78 0.78 0.86 0.88 0.86 0.85 0.78 0.84 0.76 0.76

fa.parallel(bfi)

## Parallel analysis suggests that the number of factors =  6  and the number of components =  6

bfi.fa <- fa(bfi, nfactors = 6, fm="pa", max.iter = 100)
## Loading required namespace: GPArotation

fa.diagram(bfi.fa)