Scatterplot: Compare statistics plot

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From the Plots menu, this enables the simple graphical or tabular comparison of equivalent statistics from two runs using a scatterplot (xyplot).

 

 

To automatically produce this Excel scatterplot of two sets of measures or fits statistics:

Select Compare Statistics on the Plots pull-down menu. If this dialog box is too big for your screen see Display too big.

 

 

Measures, standard errors, fit statistics indicate which statistics are to be compared.

 

Display with columns generates a line-printer graphical-columns plot. It is displayed as Table 34.

The first column is the Outfit Mean-Square of this analysis.

The third column is the Outfit Mean-Square of the Right File (exam12lopf.txt in this case)

The second column is the difference.

The fourth column is the identification, according to the current analysis.

Persons or items are matched and listed by Entry number.

 

Table 34.1

+-----------------------------------------------------------------------------+

|      PERSON       | Outfit MnSq Difference  |  exam12lopf.txt   | File Compa|

|0     1           3|-2          0           2|0     1           3| NUM  LABEL|

|-------------------+-------------------------+-------------------+-----------|

|      .   *        |      *     .            |   *  .            |  1  21101 |

|      .       *    |         *  .            |      .     *      |  2  21170 |

|  *   .            |            .*           |   *  .            |  3  21174 |

....

|     *.            |            *            |     *.            | 35  22693 |

+-----------------------------------------------------------------------------+

 

Display with Excel scatterplot initiates a graphical scatterplot plot. If the statistics being compared are both measures, then a 95% confidence interval is shown. This plot can be edited with all Excel tools.

 


 

Comparing with files

 

 

One or both sets of statistics can be in a IFILE= or PFILE= file (red arrow). Since these files can have different formats, please check that the selected field number matches the correct field in your file by clicking on the Display button (blue arrow). This displays the file. Count across the numerical fields to your selected statistic. If your field number differs from the standard field number, please provide the correct details for your field in the selection box (orange box).

 


 

There are several decisions to make:

1. Do you want to plot person (row) or item (column) statistics?

2. Which statistic for the x-axis?

3. Which statistic for the y-axis?

4. Do you want to use the statistic from this analysis or from the PFILE= or IFILE= of another analysis?

5. Do you want to display in the statistics as Columns in a Table or as an Excel scatterplot or both?

 

If you are using the statistic from a PFILE= or IFILE= and Winsteps selects the wrong column, then identify the correct column using the "Statistic field number" area.

 

When two measures are compared, then their standard errors are used to construct confidence bands when "Plot confidence bands" is checked:

 

 

Here the item calibrations in the current analysis are being compared with the item calibrations in file IFILE=SFIF.txt from another analysis. This is the columnar output:

 

TABLE 34.1 An MCQ Test: administration was Comput ZOU630WS.TXT Apr 21  2:21 2006

INPUT: 30 STUDENTS  69 TOPICS  REPORTED: 30 STUDENTS  69 TOPICS  2 CATS     3.60.2

--------------------------------------------------------------------------------

+----------------------------------------------------------------------------------------------------+

|     Measures      |       Differences        |     Measures      | Comparison                      |

|                   |                          |     SFIF.txt      |                                 |

|-4                1|-2                       5|-3                2| NUM TOPIC                       |

|-------------------+--------------------------+-------------------+---------------------------------|

|   *          .    |       .         *        |          *.       |  1  nl01  Month                 |

|              .  * |  *    .                  |         * .       |  2  nl02  Sign                  |

|    *         .    |       .          *       |           .*      |  3  nl03  Phone number          |

|  *           .    |       .                * |           .    *  |  4  nl04  Ticket                |

|    *         .    |       .                 *|           .      *|  5  nl05  building              |

|*             .    |       .              *   |           .*      |  6  nm01  student ticket        |

|        *     .    |       .        *         |           .  *    |  7  nm02  menu                  |

|       *      .    |       .           *      |           .   *   |  8  nm03  sweater               |

|        *     .    |       .        *         |           . *     |  9  nm04  Forbidden City        |

|   *          .    |       .      *           |      *    .       | 10  nm05  public place          |

|       *      .    |       .   *              |        *  .       | 11  nm06  post office           |

|   *          .    |       .    *             |     *     .       | 12  nm07  sign on wall          |

|          *   .    |       *                  |       *   .       | 13  nh01  supermarket           |

|         *    .    |       .      *           |           .*      | 14  nh02  advertisement         |

|              .*   |    *  .                  |         * .       | 15  nh03  vending machine       |

|        *     .    |       .       *          |           .*      | 16  nh04  outside store         |

|              *    |       *                  |           *       | 17  nh05  stairway              |

|        *     .    |    *  .                  | *         .       | 18  nh06  gas station           |

|          *   .    |    *  .                  |   *       .       | 19  nh07  Taipei                |

|         *    .    |       .         *        |           .    *  | 20  nh08  window at post office |

|              *    |     * .                  |        *  .       | 21  nh09  weather forecast      |

|          *   .    |       .   *              |           *       | 22  nh10  section of newspaper  |

|         *    .    |       .           *      |           .     * | 23  nh11  exchange rate         |

|             *.    |       *                  |          *.       | 24  il01  open                  |

|            * .    |       .   *              |           .*      | 25  il02  vending machine       |

+----------------------------------------------------------------------------------------------------+

 

and the plotted output:

 

We are selecting only the first 4 characters of the item label, e.g., "nl01" and plotting only the Label:

 

1. Plots with confidence bands:

 

 

The points are plotted by their labels. The curved lines are the approximate 95% two-sided confidence bands (smoothed across all the points). They are not straight because the standard errors of the points differ. In this plot called "Plot-Empirical line" (red arrow), the dotted line is the empirical equivalence (best-fit) line. Right-click on a line to reformat or remove it.

 

 

 

A line parallel to the identity line is shown on the "Plot-Identity line" (blue arrow) by selecting the tab on the bottom of the Excel screen. This line is parallel to the standard identity line (of slope 1), but goes through the origin of the two axes. This parallel-identity line goes through the mean of the two sets of measures (vertical and horizontal).

 

 

The plotted points are in the Excel Worksheet (green arrow). You can edit the data points and make any other changes you want to the plots.

 

The relationship between the variables is summarized in the lower cells.

Empirical slope = S.D.(y-values) / S.D.(x-values)

Intercept = intersection of the line with  empirical slope through the point: mean(x-values), mean(y-values)

Predicted y-value = intercept with y-axis + x-value * empirical slope

Predicted x-value = intercept with x-axis + y-value / empirical slope

 

Disattenuated correlation approximates the "true" correlation without measurement error.

Disattenuated correlation = Correlation / sqrt (Reliability(x-values) * Reliability(y-values))

 

In Row 1, the worksheet allows for user-adjustable confidence bands.

 

2. Plots without confidence bands

 

The plot can be edited with the full functionality of Excel.

 

The Worksheet shows the correlation of the points on the two axes.