Print Output from Item Analysis to Screen

Description

The function takes an ItemAnalysis object, created by the ItemAnalysis() function, and prints out Cronbach Alpha and Item to Factor Loadings, suggesting item deletions if necessary.

Usage

## S3 method for class 'ItemAnalysis'
print(x, ...)

Arguments

Details

Threshold for item deletion should have been defined in advance, when applying the PreProc() function.

Author(s)

Nikolaos Giallousis, psierevn@gmail.com

Examples

data(Depression98)
depressionScale <- Scale(data=Depression98, 
                         orders=list(
                           c(16,19,11,9,1,17,5,18,4,8,2,12,
                             20,10,14,6,3,13,15,7),
                           c(1,18,4,15,7,8,3,14,20,6,19,16,
                             12,5,10,13,2,17,11,9)),
                         orders_id=c(
                           rep(1, 49),
                           rep(2, 49)),
                         reverse=c(3,4,13,14,18,20),
                         col_names= paste('q', 1:20, sep=''))

depressionPre <- PreProc(depressionScale)

depressionRel <- ItemAnalysis(depressionPre)
print(depressionRel)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(Scale)
Loading required package: psych
Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2

Attaching package: 'ggplot2'

The following objects are masked from 'package:psych':

    %+%, alpha


Attaching package: 'Hmisc'

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

    describe

The following objects are masked from 'package:base':

    format.pval, round.POSIXt, trunc.POSIXt, units

Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Scale/print.ItemAnalysis.Rd_%03d_medium.png", width=480, height=480)
> ### Name: print.ItemAnalysis
> ### Title: Print Output from Item Analysis to Screen
> ### Aliases: print.ItemAnalysis
> ### Keywords: survey multivariate
> 
> ### ** Examples
> 
> data(Depression98)
> depressionScale <- Scale(data=Depression98, 
+                          orders=list(
+                            c(16,19,11,9,1,17,5,18,4,8,2,12,
+                              20,10,14,6,3,13,15,7),
+                            c(1,18,4,15,7,8,3,14,20,6,19,16,
+                              12,5,10,13,2,17,11,9)),
+                          orders_id=c(
+                            rep(1, 49),
+                            rep(2, 49)),
+                          reverse=c(3,4,13,14,18,20),
+                          col_names= paste('q', 1:20, sep=''))
> 
> depressionPre <- PreProc(depressionScale)
Warning message:
In PreProc(depressionScale) :
  Items' vector unspecified. out$items is NULL...
> 
> depressionRel <- ItemAnalysis(depressionPre)
> print(depressionRel)

Reliability Analysis of depressionPre ScaleData object. 

A spearman correlation matrix of 20 items was calculated and submitted to Reliability analysis.
      
The overall Cronbach's Alpha was 0.83 .
Item(s) that exhibited low correlation with the rest of the scale were:
 1 and 3 .
Furthermore, deleting item(s) 1 and 3 may improve reliability.A gls factor analysis was conducted. Items were regressed to
      a single factor. Their loadings are the following:
       q1        q3       q15        q4       q13       q19        q8        q6 
0.2265837 0.2900250 0.3400521 0.4109354 0.4173177 0.4259260 0.4320918 0.4347683 
      q16       q17       q14       q10        q7       q18        q2       q20 
0.4515751 0.4582502 0.4727368 0.4729194 0.4816417 0.4997000 0.4998320 0.5111198 
       q5        q9       q11       q12 
0.5168634 0.5349238 0.5471951 0.6541123 
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>