compPlot: Function to create comparison Plots

In qualityTools: Statistical Methods for Quality Science

Description

compPlot creates comparison x-y plots of an object of class gageRR.
The averages of the multiple readings by each operator on each part are plotted against each
other with the operators as indices. This plot compares the values obtained by one operator
to those of another.

Usage

compPlot(x, main, xlab, ylab, col, cex.lab, fun = NULL, ...)

Arguments

x	needs to be an object of class gageRR.
main	a main title for the plot
xlab	a label for the x axis
ylab	a label for the y axis
col	plotting color
cex.lab	the magnification to be used for x and y labels relative to the current setting of cex
fun	(optional) function that will be applied to the multiple readings of each part. fun should be an object of class function like mean,median, sum, etc. By default, fun is set to ‘NULL’ and all readings will be plotted.
...	arguments to be passed to methods, such as graphical parameters (see par).

Note

Please do read the vignette for the package qualityTools at http://www.r-qualitytools.org.

Author(s)

Thomas Roth: [e-mail]
Etienne Stockhausen: [e-mail]

References

The idea of the plot and the example given by example(compPlot) are out of:

• CHRYSLER Group LLC; FORD Motor Company; GENERAL MOTORS Corporation: Measurement System Analysis (MSA),
  p.115, 4rd ed. Southfield: AIAG, 2010.
  

See Also

gageRR
par
http://www.r-qualitytools.org

Examples

#create gageRR-object
gdo = gageRRDesign(Operators = 3, Parts = 10, Measurements = 3, 
      randomize = FALSE)
#vector of responses       
y = c(0.29,0.08, 0.04,-0.56,-0.47,-1.38,1.34,1.19,0.88,0.47,0.01,0.14,-0.80,       
      -0.56,-1.46, 0.02,-0.20,-0.29,0.59,0.47,0.02,-0.31,-0.63,-0.46,2.26,
      1.80,1.77,-1.36,-1.68,-1.49,0.41,0.25,-0.11,-0.68,-1.22,-1.13,1.17,0.94,
      1.09,0.50,1.03,0.20,-0.92,-1.20,-1.07,-0.11, 0.22,-0.67,0.75,0.55,0.01,
      -0.20, 0.08,-0.56,1.99,2.12,1.45,-1.25,-1.62,-1.77,0.64,0.07,-0.15,-0.58,
      -0.68,-0.96,1.27,1.34,0.67,0.64,0.20,0.11,-0.84,-1.28,-1.45,-0.21,0.06,
      -0.49,0.66,0.83,0.21,-0.17,-0.34,-0.49,2.01,2.19,1.87,-1.31,-1.50,-2.16)
#appropriate responses      
response(gdo)=y  
#perform and gageRR                                                                  
gdo=gageRR(gdo)                                                                    
compPlot(gdo,pch=19)                                                            

Example output

Loading required package: Rsolnp
Loading required package: MASS

Attaching package: 'qualityTools'

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

    sigma


AnOVa Table -  crossed Design
              Df Sum Sq Mean Sq F value   Pr(>F)    
Operator       2   3.17   1.584  34.440 1.09e-10 ***
Part           9  88.36   9.818 213.517  < 2e-16 ***
Operator:Part 18   0.36   0.020   0.434    0.974    
Residuals     60   2.76   0.046                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

----------
AnOVa Table Without Interaction -  crossed Design
            Df Sum Sq Mean Sq F value   Pr(>F)    
Operator     2   3.17   1.584   39.62 1.34e-12 ***
Part         9  88.36   9.818  245.61  < 2e-16 ***
Residuals   78   3.12   0.040                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

----------

Gage R&R
                 VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR           0.0914         0.0776 0.302     1.81           0.279
 repeatability    0.0400         0.0339 0.200     1.20           0.184
 reproducibility  0.0515         0.0437 0.227     1.36           0.209
   Operator       0.0515         0.0437 0.227     1.36           0.209
   Operator:Part  0.0000         0.0000 0.000     0.00           0.000
Part to Part      1.0864         0.9224 1.042     6.25           0.960
totalVar          1.1779         1.0000 1.085     6.51           1.000

---
 * Contrib equals Contribution in %
 **Number of Distinct Categories (truncated signal-to-noise-ratio) = 4 

NULL

qualityTools documentation built on May 2, 2019, 10:21 a.m.