[R] Data transformation for chi-square test.

[Christoph Buser]

Dear Charlie

dat <- data.frame(id = 1:10, member = c(4,2,3,5,6,2,4,6,3,4),
                  cost = c(320,150,420,330,540,310,169,647,347,567))  

dat[,"costF"] <- cut(dat[,"cost"], breaks = seq(100, 700, by=100))
table(dat[,"costF"], dat[,"member"])

This should create the table you like.

Best regards,

Christoph

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Christoph Buser <buser at stat.math.ethz.ch>
Seminar fuer Statistik, LEO C13
ETH Zurich	8092 Zurich	 SWITZERLAND
phone: x-41-44-632-4673		fax: 632-1228
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Charlie Chi writes:
 > Dear all R users
 > :
 > I am a IT student with few statistical background and new R user for only 
 > have  two month exprience. I have a data named medcost, import by 
 > read.table() as follow for example (real dataset has 500 cases), the 
 > heander id means case id, member means members in a family and cost is the 
 > family pay for medical cost every 6 months.
 > 
 > id        member               cost
 > 1         4                          320
 > 2         2                          150
 > 3         3                          420
 > 4         5                          330
 > 5         6                          540
 > 6         2                          310
 > 7         4                          169
 > 8         6                          647
 > 9         3                          347
 > 10       4                          567
 > 
 > I would like to use this dataset with chi-sqare analysis to see if there is 
 > any realationship between family member and medical cost (more members in a 
 > family will rise their medical cost?) I have found the pacage called stats, 
 > but I think need to transform the dataset into a contingency table as I 
 > read from books. I am not sure if I correct, I think the table should looks 
 > like:
 >                       member
 > cost                [2]      [3]     [4]     [5]     [6]     Total
 > [0,100]           1         0        0        0       0          1
 > [100,200]       0         0        1        0       0          1
 > [200,300]       0         0        0        0       0          0
 > [300,400]       1         1        1        1       0          4
 > [400,500]       0         1        0        0       0          1
 > [500,600]       0         0        1        0       1          2
 > [600,700]       0         0        0        0       1          1
 > Total              2          2       3         1       2         10
 > 
 > I did try to use the method in chapter 5.0 of "R Introduction" to create 
 > freqency table, but it did not work. I am wondering if any one can help me 
 > with it? Thank you for your help.
 > 
 > Regards
 > 
 > Charlie
 > ..
 > 
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