# gageLin: Function to visualize and calucalte the linearity of a gage. In qualityTools: Statistical Methods for Quality Science

## Description

Function visualize the linearity of a gage by plotting the single and mean bias in one plot and intercalate them with a straight line.
Furthermore the function deliver some characteristic values of linearity studies according to MSA (Measurement System Analysis).

## Usage

 ```1 2``` ```gageLin(object, conf.level = 0.95, ylim, col, pch, lty = c(1, 2), stats = TRUE, plot = TRUE) ```

## Arguments

 `object` an object of class `MSALinearity`. To create such an object see `gageLinDesign`. `conf.level` an numeric value between ‘0’ and ‘1’, giving the confidence intervall for the analysis. Default value: ‘0.95’ `ylim` a vector with two entries, giving the minimum and the maximum of the y-axis. `col` a vector with four numeric entries. The first gives the color of the single points, the second gives the color of the points for the mean bias, the third gives the color fo the straight interpolation line and the fourth gives the color for the lines representing the confidence interval. If one of the values is missing or negative the points or lines are not plotted. `col` is by default ‘c(1,2,1,4)’ `pch` a vector with two numeric or single character entries giving the symbols for the single points (1st entry) and the mean bias (2nd entry). The default vector is “c(20,18)” `lty` a vector with two entries giving the line-style for the interpolating line and the confidence interval lines. For detailed information to the entries please see `par`. The default value for `lty` is ‘c(1,2)’. `stats` a logigal value. If ‘TRUE’ (default) the function returns all calculated information. `plot` a logigal value. If ‘TRUE’ (default) the function deliver a plot.

## Value

The function returns an object of class `MSALinearity` which can be used with e.g. `plot` or `summary`.

## Author(s)

Thomas Roth: [email protected]
Etienne Stockhausen: [email protected]

## References

• Cgrysler Group LCC & Ford Motor Company & General Motors Corporation, Measurement System Analysis - MSA (2010), 4th ed. Southfield,Michigan: Automotive Industry Action Group.

`cg`
`gageRR`
`gageLinDesign`
`response`
`edit`
http://www.r-qualitytools.org

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```# Results of single runs A=c(2.7,2.5,2.4,2.5,2.7,2.3,2.5,2.5,2.4,2.4,2.6,2.4) B=c(5.1,3.9,4.2,5,3.8,3.9,3.9,3.9,3.9,4,4.1,3.8) C=c(5.8,5.7,5.9,5.9,6,6.1,6,6.1,6.4,6.3,6,6.1) D=c(7.6,7.7,7.8,7.7,7.8,7.8,7.8,7.7,7.8,7.5,7.6,7.7) E=c(9.1,9.3,9.5,9.3,9.4,9.5,9.5,9.5,9.6,9.2,9.3,9.4) # creates Desing test=gageLinDesign(ref=c(2,4,6,8,10),n=12) # creates data.frame with results Messungen=data.frame(rbind(A,B,C,D,E)) # enter results in Desing response(test)=Messungen # no plot and no return MSALin=gageLin(test,stats=FALSE,plot=FALSE) # plot only plot(MSALin) # summary summary(MSALin) ```

### Example output

```Loading required package: Rsolnp

Attaching package: 'qualityTools'

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

sigma

----------------------
Part Ref  X1  X2  X3  X4  X5  X6  X7  X8  X9 X10 X11 X12
A    1   2 2.7 2.5 2.4 2.5 2.7 2.3 2.5 2.5 2.4 2.4 2.6 2.4
B    2   4 5.1 3.9 4.2 5.0 3.8 3.9 3.9 3.9 3.9 4.0 4.1 3.8
C    3   6 5.8 5.7 5.9 5.9 6.0 6.1 6.0 6.1 6.4 6.3 6.0 6.1
D    4   8 7.6 7.7 7.8 7.7 7.8 7.8 7.8 7.7 7.8 7.5 7.6 7.7
E    5  10 9.1 9.3 9.5 9.3 9.4 9.5 9.5 9.5 9.6 9.2 9.3 9.4
----------------------

Call:
lm(formula = BIAS ~ ref)

Residuals:
Min       1Q   Median       3Q      Max
-0.41000 -0.12000  0.01667  0.11667  0.89000

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.73667    0.07252   10.16 1.73e-14 ***
ref         -0.13167    0.01093  -12.04  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.2395 on 58 degrees of freedom
Multiple R-squared:  0.7143,	Adjusted R-squared:  0.7094
F-statistic:   145 on 1 and 58 DF,  p-value: < 2.2e-16

----------------------
Linearity:
13.16667
```

qualityTools documentation built on May 30, 2017, 1:43 a.m.