I guess you can get the result by
1) concatenating all the variables (P2_A, P2_B, P2_C) into one variable ,
2) replicating segment membership properly,
3) make the table of 1) and 2)
For example, the following may do the job.
> ## (1) Generate data set
> # Set random seed
> set.seed(0)
>
> n.obs <- 15 # Number of patients
> disease.lv <- 1:10 ## different types of disease
> data1 <- as.data.frame(t(replicate(n.obs, sample(disease.lv, 3)))) #
Create data set
> ## Create segment membership
> segment <- sample(LETTERS[1:3], n.obs, replace=TRUE)
>
> cbind(data1, segment)
V1 V2 V3 segment
1 9 3 10 B
2 6 9 2 C
3 9 10 6 A
4 7 1 2 B
5 2 7 4 C
6 8 5 6 C
7 10 4 7 B
8 10 2 6 C
9 2 3 4 B
10 1 4 7 A
11 4 5 9 A
12 5 2 7 A
13 7 8 1 A
14 8 4 7 B
15 7 8 5 B
>
>
> ## (2) Table
> infec.all <- unlist(data1) # Concatenate all variables into one variable
> segment.all <- rep(segment, ncol(data1)) # Replicate the segment
membership as necessary
> table(infec.all, segment.all)
segment.all
infec.all A B C
1 2 1 0
2 1 2 3
3 0 2 0
4 2 3 1
5 2 1 1
6 1 0 3
7 3 4 1
8 1 2 1
9 2 1 1
10 1 2 1
On Nov 30, 2007 10:10 AM, Alejandro Rodríguez <[EMAIL PROTECTED]>
wrote:
> Hello, I'm new using R and developing tables.
>
> I have a problem in developing a table. In a questionaire I made I ask
> this
> question "Please tell me the first three sympthoms caused by Respiratory
> tract infection you've caught this year", then the people answer three
> sympthoms, the first mention (Top of mind) is saved in a variable called
> "P2_A", the second mention in a variable called "P2_B" and the third
> mention
> in "P2_C". Each answer is coded with numbers like this:
>
> 1 = Flu
> 2 = Cough
> 3 = Asthma
> ....
>
> 13 = Fever
>
> I've already done a K-cluster analysis and segmented my data base. So my
> first task is to develop tables to develop tables of frequencies crossing
> Cluster vs. "P2_A" in order to know which are the top of mind products and
> their frequencies by cluster, then the second mention and third mention.
> I've used this instruction which worked well:
>
> > table(infec1,aglomera)
> aglomera
> infec1 1 2 3 4
> 1 117 88 76 83
> 2 10 10 9 7
> 3 15 11 14 14
> 4 2 0 1 1
> 5 2 3 1 0
> 6 1 0 1 0
> 8 3 3 0 1
> 9 3 1 1 0
> 11 0 0 1 1
>
> Where "infec1" is a factor of "P2_A" and "aglomera" is a factor of the
> variable "Cluster" I made. It worked well when I study them
> separately...however I would like to know the TOTAL mentions of each
> sympthom by cluster. I've done this exercise in SPSS using the "Multiple
> Response" instruction first grouping my three variables (i.e. "P2_A",
> "P2_B"
> and "P2_C") into a variable called "sick" and cross tabulating it vs.
> QCL_1
> (my cluster variable) and it gave me the table I need in this way (showed
> at
> the bottom of this mail):
>
> How can I made a table like this in R???. I've tried combining my
> variables
> in a matrix and using xtabs, ftable, table, structable and a lot of
> combination of them but I haven't had succed with any of them.
>
> Please help me with this issue, I don't want to keep using SPSS any more.
>
> Thanx in advance.
>
> P.D. Result from SPSS is shown below.
>
>
>
> * * * C R O S S T A B U L A T I O N * * *
>
> $SICK (group) mr sick
> by QCL_1 Cluster Number of Case
>
>
> QCL_1
>
> Count I
> I Row
> I Total
> I 1 I 2 I 3 I 4 I
> $SICK --------+--------+--------+--------+--------+
> 1 I 130 I 97 I 83 I 89 I 399
> Gripe, influenza, ca I I I I I 83.1
> +--------+--------+--------+--------+
> 2 I 53 I 55 I 42 I 46 I 196
> Tos de cualquier tip I I I I I 40.8
> +--------+--------+--------+--------+
> 3 I 33 I 36 I 36 I 39 I 144
> Dolor irritación I I I I I 30.0
> +--------+--------+--------+--------+
> 4 I 5 I 1 I 2 I 3 I 11
> Bronquitis I I I I I 2.3
> +--------+--------+--------+--------+
> 5 I 5 I 4 I 1 I 0 I 10
> Sinusitis I I I I I 2.1
> +--------+--------+--------+--------+
> 6 I 1 I 1 I 1 I 3 I 6
> Rinitis I I I I I 1.3
> +--------+--------+--------+--------+
> 8 I 8 I 6 I 4 I 4 I 22
> Amigdalitis I I I I I 4.6
> +--------+--------+--------+--------+
> 9 I 6 I 4 I 1 I 2 I 13
> Faringitis I I I I I 2.7
> +--------+--------+--------+--------+
> 10 I 1 I 2 I 2 I 3 I 8
> Laringitis I I I I I 1.7
> +--------+--------+--------+--------+
> 11 I 1 I 1 I 1 I 1 I 4
> Neumonia I I I I I .8
> +--------+--------+--------+--------+
> 13 I 0 I 0 I 1 I 0 I 1
> Asma I I I I I .2
> +--------+--------+--------+--------+
> Column 153 116 104 107 480
> Total 31.9 24.2 21.7 22.3 100.0
>
> Percents and totals based on respondents
>
> 480 valid cases; 0 missing cases
>
>
>
> Act. Calef Alejandro Rodríguez Cuevas
> Analista de mercado
>
> Laboratorios Farmasa S.A. de C.V.
> Schwabe Mexico, S.A. de C.V.
>
> Bufalo Nr. 27
> Col. del Valle 03100
> Mexico, D.F.
> Mexico
>
> Tel. 52 00 26 80
> email: [EMAIL PROTECTED]
>
> www.schwabe.com.mx
> www.umckaloabo.com.mx
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
======================================
T.K. (Tae-kyun) Kim
Ph.D. student
Department of Marketing
Marshall School of Business
University of Southern California
======================================
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