Class: Statsample::Reliability::ItemAnalysis

Inherits:
Object
  • Object
show all
Defined in:
lib/statsample/reliability.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(ds) ⇒ ItemAnalysis 



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# File 'lib/statsample/reliability.rb', line 63

def initialize(ds)
  @ds=ds.dup_only_valid
  @total=@ds.vector_sum
  @item_mean=@ds.vector_mean.mean
  @mean=@total.mean
  @median=@total.median
  @skew=@total.skew
  @kurtosis=@total.kurtosis
  @sd = @total.sd
  @valid_n = @total.size
  begin
    @alpha = Statsample::Reliability.cronbach_alpha(ds)
    @alpha_standarized = Statsample::Reliability.cronbach_alpha_standarized(ds)
  rescue => e
    raise DatasetException.new(@ds,e), "Problem on calculate alpha"
  end
end

Instance Attribute Details

#alpha ⇒ Object (readonly)

Returns the value of attribute alpha.



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# File 'lib/statsample/reliability.rb', line 62

def alpha
  @alpha
end

#alpha_standarized ⇒ Object (readonly)

Returns the value of attribute alpha_standarized.



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# File 'lib/statsample/reliability.rb', line 62

def alpha_standarized
  @alpha_standarized
end

#mean ⇒ Object (readonly)

Returns the value of attribute mean.



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# File 'lib/statsample/reliability.rb', line 62

def mean
  @mean
end

#sd ⇒ Object (readonly)

Returns the value of attribute sd.



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# File 'lib/statsample/reliability.rb', line 62

def sd
  @sd
end

#valid_n ⇒ Object (readonly)

Returns the value of attribute valid_n.



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# File 'lib/statsample/reliability.rb', line 62

def valid_n
  @valid_n
end

Instance Method Details

#gnuplot_item_characteristic_curve(directory, base = "crd", options = {}) ⇒ Object 



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# File 'lib/statsample/reliability.rb', line 104

def gnuplot_item_characteristic_curve(directory, base="crd",options={})
  require 'gnuplot'

  crd=item_characteristic_curve
  @ds.fields.each  do |f|
    x=[]
    y=[]
    Gnuplot.open do |gp|
      Gnuplot::Plot.new( gp ) do |plot|
        crd[f].sort.each do |tot,prop|
          x.push(tot)
          y.push((prop*100).to_i.to_f/100)
        end
        plot.data << Gnuplot::DataSet.new( [x, y] ) do |ds|
          ds.with = "linespoints"
          ds.notitle
        end

      end
    end
  end
end

#html_summary ⇒ Object 



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# File 'lib/statsample/reliability.rb', line 204

def html_summary
        html = "<p><strong>Summary for scale:</strong></p>\n<ul>\n<li>Items=\#{@ds.fields.size}</li>\n<li>Total Mean=\#{@mean}</li>\n<li>Item Mean=\#{@item_mean}</li>\n<li>Std.Dv.=\#{@sd}</li>\n<li>Median=\#{@median}</li>\n<li>Skewness=\#{sprintf(\"%0.3f\",@skew)}</li>\n<li>Kurtosis=\#{sprintf(\"%0.3f\",@kurtosis)}</li>\n\n<li>Valid n:\#{@valid_n}</li>\n<li>Cronbach alpha: \#{@alpha}</li>\n</ul>\n<table><thead><th>Variable</th>\n\n<th>Mean</th>\n<th>StDv.</th>\n<th>Mean if deleted</th><th>Var. if\ndeleted</th><th>  StDv. if\ndeleted</th><th>  Itm-Totl\nCorrel.</th><th>Alpha if\ndeleted</th></thead>\n"

  itc=item_total_correlation
  sid=stats_if_deleted
  is=item_statistics
  @ds.fields.each {|f|
    html << "    <tr>\n    <td>\#{f}</td>\n    <td>\#{sprintf(\"%0.5f\",is[f][:mean])}</td>\n    <td>\#{sprintf(\"%0.5f\",is[f][:sds])}</td>\n    <td>\#{sprintf(\"%0.5f\",sid[f][:mean])}</td>\n    <td>\#{sprintf(\"%0.5f\",sid[f][:variance_sample])}</td>\n    <td>\#{sprintf(\"%0.5f\",sid[f][:sds])}</td>\n    <td>\#{sprintf(\"%0.5f\",itc[f])}</td>\n    <td>\#{sprintf(\"%0.5f\",sid[f][:alpha])}</td>\n    </tr>\n"
  }
  html << "</table><hr />"
  html
end

#item_characteristic_curve ⇒ Object

Returns a hash with structure



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# File 'lib/statsample/reliability.rb', line 81

def item_characteristic_curve
  i=0
  out={}
  total={}
  @ds.each do |row|
    tot=@total[i]
    @ds.fields.each do |f|
      out[f]||= {}
      total[f]||={}
      out[f][tot]||= 0
      total[f][tot]||=0
      out[f][tot]+= row[f]
      total[f][tot]+=1
    end
    i+=1
  end
  total.each do |f,var|
    var.each do |tot,v|
      out[f][tot]=out[f][tot].to_f / total[f][tot]
    end
  end
  out
end

#item_difficulty_analysis ⇒ Object

Returns a dataset with cases ordered by score and variables ordered by difficulty



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# File 'lib/statsample/reliability.rb', line 173

def item_difficulty_analysis
  dif={}
  @ds.fields.each{|f| dif[f]=@ds[f].mean }
  dif_sort=dif.sort{|a,b| -(a[1]<=>b[1])}
  scores_sort={}
  scores=@ds.vector_mean
  scores.each_index{|i| scores_sort[i]=scores[i] }
  scores_sort=scores_sort.sort{|a,b| a[1]<=>b[1]}
  ds_new=Statsample::Dataset.new(['case','score'] + dif_sort.collect{|a,b| a})
  scores_sort.each do |i,score|
    row=[i, score]
    case_row=@ds.case_as_hash(i)
    dif_sort.each{|variable,dif_value| row.push(case_row[variable]) }
    ds_new.add_case_array(row)
  end
  ds_new.update_valid_data
  ds_new
end

#item_statistics ⇒ Object 



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# File 'lib/statsample/reliability.rb', line 164

def item_statistics
  @ds.fields.inject({}) do |a,v|
    a[v]={:mean=>@ds[v].mean,:sds=>@ds[v].sds}
    a
  end
end

#item_total_correlation ⇒ Object 



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# File 'lib/statsample/reliability.rb', line 154

def item_total_correlation
  @ds.fields.inject({}) do |a,v|
    vector=@ds[v].dup
    ds2=@ds.dup
    ds2.delete_vector(v)
    total=ds2.vector_sum
    a[v]=Statsample::Bivariate.pearson(vector,total)
    a
  end
end

#stats_if_deleted ⇒ Object 



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# File 'lib/statsample/reliability.rb', line 191

def stats_if_deleted
  @ds.fields.inject({}) do |a,v|
    ds2=@ds.dup
    ds2.delete_vector(v)
    total=ds2.vector_sum
    a[v]={}
    a[v][:mean]=total.mean
    a[v][:sds]=total.sds
    a[v][:variance_sample]=total.variance_sample
    a[v][:alpha]=Statsample::Reliability.cronbach_alpha(ds2)
    a
  end
end

#svggraph_item_characteristic_curve(directory, base = "icc", options = {}) ⇒ Object 



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# File 'lib/statsample/reliability.rb', line 126

def svggraph_item_characteristic_curve(directory, base="icc",options={})
  require 'statsample/graph/svggraph'
  crd=ItemCharacteristicCurve.new(@ds)
  @ds.fields.each do |f|
    factors=@ds[f].factors.sort
    options={
      :height=>500,
      :width=>800,
      :key=>true
    }.update(options)
    graph = ::SVG::Graph::Plot.new(options)
    factors.each do |factor|
      factor=factor.to_s
      dataset=[]
      crd.curve_field(f, factor).each do |tot,prop|
        dataset.push(tot)
        dataset.push((prop*100).to_i.to_f/100)
      end
      graph.add_data({
        :title=>"#{factor}",
        :data=>dataset
      })
    end
    File.open(directory+"/"+base+"_#{f}.svg","w") {|fp|
      fp.puts(graph.burn())
    }
  end
end