This example uses the Office Visits.jmp sample data table, which records late and on-time appointments for six clinics in a geographic region. 60 random appointments were selected from 1 week of records for each of the six clinics. To be considered on-time, the patient must be taken to an exam room within five minutes of their scheduled appointment time. Examine the proportion of patients that arrived on-time to their appointment.
1.
Open the Office Visits.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select On Time and click Y, Response.
4.
Select Clinic and click X, Factor.
5.
Select Frequency and click Freq.
6.
Example of Analysis of Means for Proportions
Example of Analysis of Means for Proportions shows the proportion of patients who were on-time from each clinic. From Example of Analysis of Means for Proportions, notice the following:
This example uses the Cheese.jmp sample data table, which is taken from the Newell cheese tasting experiment, reported in McCullagh and Nelder (1989). The experiment records counts more than nine different response levels across four different cheese additives.
1.
Open the Cheese.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select Response and click Y, Response.
The Response values range from one to nine, where one is the least liked, and nine is the best liked.
4.
Select Cheese and click X, Factor.
5.
Select Count and click Freq.
6.
Mosaic Plot for the Cheese Data
From the mosaic plot in Mosaic Plot for the Cheese Data, you notice that the distributions do not appear alike. However, it is challenging to make sense of the mosaic plot across nine levels. A correspondence analysis can help define relationships in this type of situation.
Example of a Correspondence Analysis Plot
Example of a Correspondence Analysis Plot shows the correspondence analysis graphically, with the plot axes labeled c1 and c2. Notice the following:
Example of a 3-D Scatterplot
From Example of a 3-D Scatterplot, notice the following:
This example uses the Mail Messages.jmp sample data table, which contains data about e-mail messages that were sent and received. The data includes the time, sender, and receiver. Examine the pattern of e-mail senders and receivers.
1.
Open the Mail Messages.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select To and click Y, Response.
4.
Select From and click X, Factor.
5.
Contingency Analysis for E-mail Data
Correspondence Analysis for E-mail Data
The Correspondence Analysis plot of c1 and c2 shows the pattern of mail distribution among the mail group, as follows:
This example uses the Hot Dogs.jmp sample data table. Examine the relationship between hot dog type and taste.
1.
Open the Hot Dogs.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select Type and click Y, Response.
4.
Select Taste and click X, Factor.
5.
7.
Select Protein/Fat as the grouping variable and click OK.
Example of a Cochran-Mantel-Haenszel Test
This example uses the Attribute Gauge.jmp sample data table. The data gives results from three people (raters) rating fifty parts three times each. Examine the relationship between raters A and B.
1.
Open the Attribute Gauge.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select A and click Y, Response.
4.
Select B and click X, Factor.
5.
Example of the Agreement Statistic Report
From Example of the Agreement Statistic Report, you notice that the agreement statistic of 0.86 is high (close to 1) and the p-value of <.0001 is small. This reinforces the high agreement seen by looking at the diagonal of the contingency table. Agreement between the raters occurs when both raters give a rating of 0 or both give a rating of 1.
This example uses the Car Poll.jmp sample data table. Examine the relative probabilities of being married and single for the participants in the poll.
1.
Open the Car Poll.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select marital status and click Y, Response.
4.
Select sex and click X, Factor.
5.
The Choose Relative Risk Categories Window
7.
Ask for all combinations by selecting the Calculate All Combinations check box. Leave all other default selections as is.
Example of the Risk Ratio Report
This example uses the Car Poll.jmp sample data table. Examine the probability of being married for males and females.
1.
Open the Car Poll.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select marital status and click Y, Response.
4.
Select sex and click X, Factor.
5.
Example of the Two Sample Test for Proportions Report
This example uses the Car Poll.jmp sample data table. Examine the probability of being married for males and females.
1.
Open the Car Poll.jmp sample data table.
2.
Select Analyze > Fit Y by X.
3.
Select marital status and click Y, Response.
4.
Select sex and click X, Factor.
5.
Example of the Measures of Association Report
1.
Open the Car Poll.jmp sample data table.
3.
Select Analyze > Fit Y by X.
4.
Select sex and click Y, Response.
5.
Select size and click X, Factor.
6.
Example of the Cochran Armitage Trend Test Report